Need for non-visual feedback with long response times in mobile HCI When browsing Web pages with a mobile device , the system response times are variable and much longer than on a PC . Users must repeatedly glance at the display to see when the page finally arrives , although mobility demands a Minimal Attention User Interface . We conducted a user study with 27 participants to discover the point at which visual feedback stops reaching the user in mobile context . In the study , we examined the deployment of attention during page loading to the phone vs. the environment in several different everyday mobility contexts , and compared these to the laboratory context . The first part of the page appeared on the screen typically in 11 seconds , but we found that the user 's visual attention shifted away from the mobile browser usually between 4 and 8 seconds in the mobile context . In contrast , the continuous span of attention to the browser was more than 14 seconds in the laboratory condition . Based on our study results , we recommend mobile applications provide multimodal feedback for delays of more than four seconds .

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O


A method for transparent admission control and request scheduling in e-commerce web sites This paper presents a method for admission control and request scheduling for multiply-tiered e-commerce Web sites , achieving both stable behavior during overload and improved response times . Our method externally observes execution costs of requests online , distinguishing different request types , and performs overload protection and preferential scheduling using relatively simple measurements and a straight forward control mechanism . Unlike previous proposals , which require extensive changes to the server or operating system , our method requires no modifications to the host O.S. , Web server , application server or database . Since our method is external , it can be implemented in a proxy . We present such an implementation , called Gatekeeper , using it with standard software components on the Linux operating system . We evaluate the proxy using the industry standard TPC-W workload generator in a typical three-tiered e-commerce environment . We show consistent performance during overload and throughput increases of up to 10 percent . Response time improves by up to a factor of 14 , with only a 15 percent penalty to large jobs .

O O O O B I O B I O O O O O O O O O O B I O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

dynamic web content
load control
web servers


Bootstrapping ontology alignment methods with APFEL

interoperability
machine learning
mapping
matching


RuralCafe : web search in the rural developing world The majority of people in rural developing regions do not have access to the World Wide Web . Traditional network connectivity technologies have proven to be prohibitively expensive in these areas . The emergence of new long-range wireless technologies provide hope for connecting these rural regions to the Internet . However , the network connectivity provided by these new solutions are by nature intermittent due to high network usage rates , frequent power-cuts and the use of delay tolerant links . Typical applications , especially interactive applications like web search , do not tolerate intermittent connectivity . In this paper , we present the design and implementation of RuralCafe , a system intended to support efficient web search over intermittent networks . RuralCafe enables users to perform web search asynchronously and find what they are looking for in one round of intermittency as opposed to multiple rounds of search\/downloads . RuralCafe does this by providing an expanded search query interface which allows a user to specify additional query terms to maximize the utility of the results returned by a search query . Given knowledge of the limited available network resources , RuralCafe performs optimizations to prefetch pages to best satisfy a search query based on a user 's search preferences . In addition , RuralCafe does not require modifications to the web browser , and can provide single round search results tailored to various types of networks and economic constraints . We have implemented and evaluated the effectiveness of RuralCafe using queries from logs made to a large search engine , queries made by users in an intermittent setting , and live queries from a small testbed deployment . We have also deployed a prototype of RuralCafe in Kerala , India .

O O B I O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

information search and retrieval
intermittent network
low bandwidth


Differences in the mechanics of information diffusion across topics : idioms , political hashtags , and complex contagion on twitter There is a widespread intuitive sense that different kinds of information spread differently on-line , but it has been difficult to evaluate this question quantitatively since it requires a setting where many different kinds of information spread in a shared environment . Here we study this issue on Twitter , analyzing the ways in which tokens known as hashtags spread on a network defined by the interactions among Twitter users . We find significant variation in the ways that widely-used hashtags on different topics spread . Our results show that this variation is not attributable simply to differences in `` stickiness , '' the probability of adoption based on one or more exposures , but also to a quantity that could be viewed as a kind of `` persistence '' - the relative extent to which repeated exposures to a hashtag continue to have significant marginal effects . We find that hashtags on politically controversial topics are particularly persistent , with repeated exposures continuing to have unusually large marginal effects on adoption ; this provides , to our knowledge , the first large-scale validation of the `` complex contagion '' principle from sociology , which posits that repeated exposures to an idea are particularly crucial when the idea is in some way controversial or contentious . Among other findings , we discover that hashtags representing the natural analogs of Twitter idioms and neologisms are particularly non-persistent , with the effect of multiple exposures decaying rapidly relative to the first exposure . We also study the subgraph structure of the initial adopters for different widely-adopted hashtags , again finding structural differences across topics . We develop simulation-based and generative models to analyze how the adoption dynamics interact with the network structure of the early adopters on which a hashtag spreads .

O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

miscellaneous
social contagion
social media


Choosing reputable servents in a P2P network Peer-to-peer information sharing environments are increasingly gaining acceptance on the Internet as they provide an infrastructure in which the desired information can be located and downloaded while preserving the anonymity of both requestors and providers . As recent experience with P2P environments such as Gnutella shows , anonymity opens the door to possible misuses and abuses by resource providers exploiting the network as a way to spread tampered with resources , including malicious programs , such as Trojan Horses and viruses . In this paper we propose an approach to P2P security where servents can keep track , and share with others , information about the reputation of their peers . Reputation sharing is based on a distributed polling algorithm by which resource requestors can assess the reliability of perspective providers before initiating the download . The approach nicely complements the existing P2P protocols and has a limited impact on current implementations . Furthermore , it keeps the current level of anonymity of requestors and providers , as well as that of the parties sharing their view on others ' reputations .

O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

credibility
invasive software
polling protocol
security and protection


A large-scale study of the evolution of web pages How fast does the web change ? Does most of the content remain unchanged once it has been authored , or are the documents continuously updated ? Do pages change a little or a lot ? Is the extent of change correlated to any other property of the page ? All of these questions are of interest to those who mine the web , including all the popular search engines , but few studies have been performed to date to answer them . One notable exception is a study by Cho and Garcia-Molina , who crawled a set of 720,000 pages on a daily basis over four months , and counted pages as having changed if their MD5 checksum changed . They found that 40 % of all web pages in their set changed within a week , and 23 % of those pages that fell into the . com domain changed daily . This paper expands on Cho and Garcia-Molina 's study , both in terms of coverage and in terms of sensitivity to change . We crawled a set of 150,836,209 HTML pages once every week , over a span of 11 weeks . For each page , we recorded a checksum of the page , and a feature vector of the words on the page , plus various other data such as the page length , the HTTP status code , etc. . Moreover , we pseudo-randomly selected 0.1 % of all of our URLs , and saved the full text of each download of the corresponding pages . After completion of the crawl , we analyzed the degree of change of each page , and investigated which factors are correlated with change intensity . We found that the average degree of change varies widely across top-level domains , and that larger pages change more often and more severely than smaller ones . This paper describes the crawl and the data transformations we performed on the logs , and presents some statistical observations on the degree of change of different classes of pages .

O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O

hypertext/hypermedia
miscellaneous
rate of change
web characterization
web evolution


Probabilistic question recommendation for question answering communities User-Interactive Question Answering ( QA ) communities such as Yahoo ! Answers are growing in popularity . However , as these QA sites always have thousands of new questions posted daily , it is difficult for users to find the questions that are of interest to them . Consequently , this may delay the answering of the new questions . This gives rise to question recommendation techniques that help users locate interesting questions . In this paper , we adopt the Probabilistic Latent Semantic Analysis ( PLSA ) model for question recommendation and propose a novel metric to evaluate the performance of our approach . The experimental results show our recommendation approach is effective .

O B I O B I O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O B O O O B I O O O O O O O O O O O O O O O O O O O O O O O

plsa
question answering
question recommendation


Design of a crawler with bounded bandwidth This paper presents an algorithm to bound the bandwidth of a Web crawler . The crawler collects statistics on the transfer rate of each server to predict the expected bandwidth use for future downloads . The prediction allows us to activate the optimal number of fetcher threads in order to exploit the assigned bandwidth . The experimental results show the effectiveness of the proposed technique .

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

bandwidth optimization
information storage and retrieval
parallel web crawlers


Groupme ! This paper presents the GroupMe ! system , a resource sharing system with advanced tagging functionality . GroupMe ! provides a novel user interface , which enables users to organize and arrange arbitrary Web resources into groups . The content of such groups can be overlooked and inspected immediately as resources are visualized in a multimedia-based fashion . In this paper , we furthermore introduce new folksonomy-based ranking strategies that exploit the group structure shipped with GroupMe ! folksonomies . Experiments show that those strategies significantly improve the performance of such ranking algorithms .

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O B O O

groupme!
miscellaneous
search
social media


Template detection via data mining and its applications We formulate and propose the template detection problem , and suggest a practical solution for it based on counting frequent item sets . We show that the use of templates is pervasive on the web . We describe three principles , which characterize the assumptions made by hypertext information retrieval ( IR ) and data mining ( DM ) systems , and show that templates are a major source of violation of these principles . As a consequence , basic `` pure '' implementations of simple search algorithms coupled with template detection and elimination show surprising increases in precision at all levels of recall .

O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B I O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

data mining
hypertext
information retrieval

information search and retrieval
web searching


Automatic extraction of clickable structured web contents for name entity queries Today the major web search engines answer queries by showing ten result snippets , which need to be inspected by users for identifying relevant results . In this paper we investigate how to extract structured information from the web , in order to directly answer queries by showing the contents being searched for . We treat users ' search trails ( i.e. , post-search browsing behaviors ) as implicit labels on the relevance between web contents and user queries . Based on such labels we use information extraction approach to build wrappers and extract structured information . An important observation is that many web sites contain pages for name entities of certain categories ( e.g. , AOL Music contains a page for each musician ) , and these pages have the same format . This makes it possible to build wrappers from a small amount of implicit labels , and use them to extract structured information from many web pages for different name entities . We propose STRUCLICK , a fully automated system for extracting structured information for queries containing name entities of certain categories . It can identify important web sites from web search logs , build wrappers from users ' search trails , filter out bad wrappers built from random user clicks , and combine structured information from different web sites for each query . Comparing with existing approaches on information extraction , STRUCLICK can assign semantics to extracted data without any human labeling or supervision . We perform comprehensive experiments , which show STRUCLICK achieves high accuracy and good scalability .

O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Video suggestion and discovery for youtube : taking random walks through the view graph The rapid growth of the number of videos in YouTube provides enormous potential for users to find content of interest to them . Unfortunately , given the difficulty of searching videos , the size of the video repository also makes the discovery of new content a daunting task . In this paper , we present a novel method based upon the analysis of the entire user-video graph to provide personalized video suggestions for users . The resulting algorithm , termed Adsorption , provides a simple method to efficiently propagate preference information through a variety of graphs . We extensively test the results of the recommendations on a three month snapshot of live data from YouTube .

O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

collaborative filtering
label propagation
recommendation systems
video search


Semantic web support for the business-to-business e-commerce lifecycle If an e-services approach to electronic commerce is to become widespread , standardisation of ontologies , message content and message protocols will be necessary . In this paper , we present a lifecycle of a business-to-business e-commerce interaction , and show how the Semantic Web can support a service description language that can be used throughout this lifecycle . By using DAML , we develop a service description language sufficiently expressive and flexible to be used not only in advertisements , but also in matchmaking queries , negotiation proposals and agreements . We also identify which operations must be carried out on this description language if the B2B lifecycle is to be fully supported . We do not propose specific standard protocols , but instead argue that our operators are able to support a wide variety of interaction protocols , and so will be fundamental irrespective of which protocols are finally adopted .

B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O B I O O O O O O O O O O O B O O O O B I O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

daml
matchmaking
semantic web
service description

automated negotiation
e-commerce
electronic data interchange


Cross-domain sentiment classification via spectral feature alignment Sentiment classification aims to automatically predict sentiment polarity ( e.g. , positive or negative ) of users publishing sentiment data ( e.g. , reviews , blogs ) . Although traditional classification algorithms can be used to train sentiment classifiers from manually labeled text data , the labeling work can be time-consuming and expensive . Meanwhile , users often use some different words when they express sentiment in different domains . If we directly apply a classifier trained in one domain to other domains , the performance will be very low due to the differences between these domains . In this work , we develop a general solution to sentiment classification when we do not have any labels in a target domain but have some labeled data in a different domain , regarded as source domain . In this cross-domain sentiment classification setting , to bridge the gap between the domains , we propose a spectral feature alignment ( SFA ) algorithm to align domain-specific words from different domains into unified clusters , with the help of domain-independent words as a bridge . In this way , the clusters can be used to reduce the gap between domain-specific words of the two domains , which can be used to train sentiment classifiers in the target domain accurately . Compared to previous approaches , SFA can discover a robust representation for cross-domain data by fully exploiting the relationship between the domain-specific and domain-independent words via simultaneously co-clustering them in a common latent space . We perform extensive experiments on two real world datasets , and demonstrate that SFA significantly outperforms previous approaches to cross-domain sentiment classification .

O B I O O B I B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O

feature alignment
sentiment classification

database applications
domain adaptation
learning
opinion mining
transfer learning


Mind the data skew : distributed inferencing by speeddating in elastic regions Semantic Web data exhibits very skewed frequency distributions among terms . Efficient large-scale distributed reasoning methods should maintain load-balance in the face of such highly skewed distribution of input data . We show that term-based partitioning , used by most distributed reasoning approaches , has limited scalability due to load-balancing problems . We address this problem with a method for data distribution based on clustering in elastic regions . Instead of as - signing data to fixed peers , data flows semi-randomly in the network . Data items `` speed-date '' while being temporarily collocated in the same peer . We introduce a bias in the routing to allow semantically clustered neighborhoods to emerge . Our approach is self-organising , efficient and does not require any central coordination . We have implemented this method on the MaRVIN platform and have performed experiments on large real-world datasets , using a cluster of up to 64 nodes . We compute the RDFS closure over different datasets and show that our clustering algorithm drastically reduces computation time , calculating the RDFS closure of 200 million triples in 7.2 minutes .

O O O O O B O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


An economic model of the worldwide web We believe that much novel insight into the worldwide web can be obtained from taking into account the important fact that it is created , used , and run by selfish optimizing agents : users , document authors , and search engines . On-going theoretical and experimental analysis of a simple abstract model of www creation and search based on user utilities illustrates this point : We find that efficiency is higher when the utilities are more clustered , and that power-law statistics of document degrees emerge very naturally in this context . More importantly , our work sets up many more elaborate questions , related , e.g. , to www search algorithms seen as author incentives , to search engine spam , and to search engine quality and competition .

O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

game theory
general
market
power laws
price of anarchy
utility function
web search


Multiway SLCA-based keyword search in XML data Keyword search for smallest lowest common ancestors ( SLCAs ) in XML data has recently been proposed as a meaningful way to identify interesting data nodes inXML data where their subtrees contain an input set of keywords . In this paper , we generalize this useful search paradigm to support keyword search beyond the traditional AND semantics to include both AND and OR boolean operators as well . We first analyze properties of the LCA computation and propose improved algorithms to solve the traditional keyword search problem ( with only AND semantics ) . We then extend our approach to handle general keyword search involving combinations of AND and OR boolean operators . The effectiveness of our new algorithms is demonstrated with a comprehensive experimental performance study .

O O O O O B O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

keyword search query
lowest common ancestor


Privacy diffusion on the web : a longitudinal perspective For the last few years we have been studying the diffusion of private information for users as they visit various Web sites triggering data gathering aggregation by third parties . This paper reports on our longitudinal study consisting of multiple snapshots of our examination of such diffusion over four years . We examine the various technical ways by which third-party aggregators acquire data and the depth of user-related information acquired . We study techniques for protecting privacy diffusion as well as limitations of such techniques . We introduce the concept of secondary privacy damage . Our results show increasing aggregation of user-related data by a steadily decreasing number of entities . A handful of companies are able to track users ' movement across almost all of the popular Web sites . Virtually all the protection techniques have significant limitations highlighting the seriousness of the problem and the need for alternate solutions .

B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

applications
privacy enhancing technologies


WAP5 : black-box performance debugging for wide-area systems Wide-area distributed applications are challenging to debug , optimize , and maintain . We present Wide-Area Project 5 ( WAP5 ) , which aims to make these tasks easier by exposing the causal structure of communication within an application and by exposing delays that imply bottlenecks . These bottlenecks might not otherwise be obvious , with or without the application 's source code . Previous research projects have presented algorithms to reconstruct application structure and the corresponding timing information from black-box message traces of local-area systems . In this paper we present ( 1 ) a new algorithm for reconstructing application structure in both local - and wide-area distributed systems , ( 2 ) an infrastructure for gathering application traces in PlanetLab , and ( 3 ) our experiences tracing and analyzing three systems : CoDeeN and Coral , two content-distribution networks in PlanetLab ; and Slurpee , an enterprise-scale incident-monitoring system .

O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

distributed systems
performance debugging

black box systems
performance analysis
testing tools


Unified analysis of streaming news News clustering , categorization and analysis are key components of any news portal . They require algorithms capable of dealing with dynamic data to cluster , interpret and to temporally aggregate news articles . These three tasks are often solved separately . In this paper we present a unified framework to group incoming news articles into temporary but tightly-focused storylines , to identify prevalent topics and key entities within these stories , and to reveal the temporal structure of stories as they evolve . We achieve this by building a hybrid clustering and topic model . To deal with the available wealth of data we build an efficient parallel inference algorithm by sequential Monte Carlo estimation . Time and memory costs are nearly constant in the length of the history , and the approach scales to hundreds of thousands of documents . We demonstrate the efficiency and accuracy on the publicly available TDT dataset and data of a major internet news site .

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

dirichlet processes
learning
online inference
topic models


Answering order-based queries over XML data Order-based queries over XML data include XPath navigation axes such as following-sibling and following . In this paper , we present holistic algorithms that evaluate such order-based queries . An experimental comparison with previous approaches shows the performance benefits of our algorithms .

O O O O B O O O O B O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O


Learning to rank relational objects and its application to web search Learning to rank is a new statistical learning technology on creating a ranking model for sorting objects . The technology has been successfully applied to web search , and is becoming one of the key machineries for building search engines . Existing approaches to learning to rank , however , did not consider the cases in which there exists relationship between the objects to be ranked , despite of the fact that such situations are very common in practice . For example , in web search , given a query certain relationships usually exist among the the retrieved documents , e.g. , URL hierarchy , similarity , etc. , and sometimes it is necessary to utilize the information in ranking of the documents . This paper addresses the issue and formulates it as a novel learning problem , referred to as , ` learning to rank relational objects ' . In the new learning task , the ranking model is defined as a function of not only the contents ( features ) of objects but also the relations between objects . The paper further focuses on one setting of the learning problem in which the way of using relation information is predetermined . It formalizes the learning task as an optimization problem in the setting . The paper then proposes a new method to perform the optimization task , particularly an implementation based on SVM . Experimental results show that the proposed method outperforms the baseline methods for two ranking tasks ( Pseudo Relevance Feedback and Topic Distillation ) in web search , indicating that the proposed method can indeed make effective use of relation information and content information in ranking .

B I I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O B I O O O O O O O O O O O O O O O O O O O O O O O O

learning to rank relational objects
pseudo relevance feedback
topic distillation

performance evaluation
relational ranking svm


Template-based question answering over RDF data As an increasing amount of RDF data is published as Linked Data , intuitive ways of accessing this data become more and more important . Question answering approaches have been proposed as a good compromise between intuitiveness and expressivity . Most question answering systems translate questions into triples which are matched against the RDF data to retrieve an answer , typically relying on some similarity metric . However , in many cases , triples do not represent a faithful representation of the semantic structure of the natural language question , with the result that more expressive queries can not be answered . To circumvent this problem , we present a novel approach that relies on a parse of the question to produce a SPARQL template that directly mirrors the internal structure of the question . This template is then instantiated using statistical entity identification and predicate detection . We show that this approach is competitive and discuss cases of questions that can be answered with our approach but not with competing approaches .

O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Predicting positive and negative links in online social networks We study online social networks in which relationships can be either positive ( indicating relations such as friendship ) or negative ( indicating relations such as opposition or antagonism ) . Such a mix of positive and negative links arise in a variety of online settings ; we study datasets from Epinions , Slashdot and Wikipedia . We find that the signs of links in the underlying social networks can be predicted with high accuracy , using models that generalize across this diverse range of sites . These models provide insight into some of the fundamental principles that drive the formation of signed links in networks , shedding light on theories of balance and status from social psychology ; they also suggest social computing applications by which the attitude of one user toward another can be estimated from evidence provided by their relationships with other members of the surrounding social network .

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

distrust
negative edges
positive edges
signed networks
status theory
structural balance
trust


The Eigentrust algorithm for reputation management in P2P networks Peer-to-peer file-sharing networks are currently receiving much attention as a means of sharing and distributing information . However , as recent experience shows , the anonymous , open nature of these networks offers an almost ideal environment for the spread of self-replicating inauthentic files . We describe an algorithm to decrease the number of downloads of inauthentic files in a peer-to-peer file-sharing network that assigns each peer a unique global trust value , based on the peer 's history of uploads . We present a distributed and secure method to compute global trust values , based on Power iteration . By having peers use these global trust values to choose the peers from whom they download , the network effectively identifies malicious peers and isolates them from the network . In simulations , this reputation system , called EigenTrust , has been shown to significantly decrease the number of inauthentic files on the network , even under a variety of conditions where malicious peers cooperate in an attempt to deliberately subvert the system .

O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

distributed eigenvector computation
peer-to-peer


On a web browsing support system with 3d visualization Existing commercial Web browsers provide various utilities and functions , e.g. , Web bookmarks and a browsing history list . Since the bookmark and history functions only the title and URL of the Web page , users who can not remember the contents of each Web page have difficulty retracing their steps . In this paper , we propose a bookmark system based on a 3D interface . Additionally , our system offers three main functions a 3D browsing history function , a marker function , and a look-ahead loading function . These functions enable users to browse Web pages more effectively .

O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

3d technology
graphical user interfaces
web browser


Finding group shilling in recommendation system In the age of information explosion , recommendation system has been proved effective to cope with information overload in e-commerce area . However , unscrupulous producers shill the systems in many ways to make profit , and it makes the system imprecise and unreliable in a long term . Among many shilling behaviors , a new form of attack , called group shilling , appears and does great harm to the system . Because group shilling users are now well organized and become more hidden among various normal users , it is hard to find them by traditional methods . However , these group shilling users are similar to some extent , for they both shill the target items . We bring out a similarity spreading algorithm to find these group shilling users and protect recommendation system from unfair ratings . In our algorithm , we try to find these cunning group shilling users through propagating similarities from items to users iteratively . The experiment shows our similarity spreading algorithm improves the precision of the system and provides the system a reliable protection .

O B I O B I O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O B I O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Certified email with a light on-line trusted third party : design and implementation This paper presents a new protocol for certified email . The protocol aims to combine security , scalability , easy implementation , and viable deployment . The protocol relies on a light on-line trusted third party ; it can be implemented without any special software for the receiver beyond a standard email reader and web browser , and does not require any public-key infrastructure .

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


The value of socially tagged urls for a search engine Social bookmarking has emerged as a growing source of human generated content on the web . In essence , bookmarking involves URLs and tags on them . In this paper , we perform a large scale study of the usefulness of bookmarked URLs from the top social bookmarking site Delicious . Instead of focusing on the dimension of tags , which has been covered in the previous work , we explore social bookmarking from the dimension of URLs . More specifically , we investigate the Delicious URLs and their content to quantify their value to a search engine . For their value in leading to good content , we show that the Delicious URLs have higher quality content and more external outlinks . For their value in satisfying users , we show that the Delicious URLs have more clicked URLs as well as get more clicks . We suggest that based on their value , the Delicious URLs should be used as another source of seed URLs for crawlers .

O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O B O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O


Mr. LDA : a flexible large scale topic modeling package using variational inference in MapReduce Latent Dirichlet Allocation ( LDA ) is a popular topic modeling technique for exploring document collections . Because of the increasing prevalence of large datasets , there is a need to improve the scalability of inference for LDA . In this paper , we introduce a novel and flexible large scale topic modeling package in MapReduce ( Mr. LDA ) . As opposed to other techniques which use Gibbs sampling , our proposed framework uses variational inference , which easily fits into a distributed environment . More importantly , this variational implementation , unlike highly tuned and specialized implementations based on Gibbs sampling , is easily extensible . We demonstrate two extensions of the models possible with this scalable framework : informed priors to guide topic discovery and extracting topics from a multilingual corpus . We compare the scalability of Mr. LDA against Mahout , an existing large scale topic modeling package . Mr. LDA out-performs Mahout both in execution speed and held-out likelihood .

O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O


Detecting image spam using local invariant features and pyramid match kernel Image spam is a new obfuscating method which spammers invented to more effectively bypass conventional text based spam filters . In this paper , we extract local invariant features of images and run a one-class SVM classifier which uses the pyramid match kernel as the kernel function to detect image spam . Experimental results demonstrate that our algorithm is effective for fighting image spam .

O B I O B I I O B I I B I O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O B I I O O O O O O B I O O O O O O O O O O O B I O

image spam
local invariant features
pyramid match kernel


Intelligent crawling of web applications for web archiving The steady growth of the World Wide Web raises challenges regarding the preservation of meaningful Web data . Tools used currently by Web archivists blindly crawl and store Web pages found while crawling , disregarding the kind of Web site currently accessed ( which leads to suboptimal crawling strategies ) and whatever structured content is contained in Web pages ( which results in page-level archives whose content is hard to exploit ) . We focus in this PhD work on the crawling and archiving of publicly accessible Web applications , especially those of the social Web . A Web application is any application that uses Web standards such as HTML and HTTP to publish information on the Web , accessible by Web browsers . Examples include Web forums , social networks , geolocation services , etc. . We claim that the best strategy to crawl these applications is to make the Web crawler aware of the kind of application currently processed , allowing it to refine the list of URLs to process , and to annotate the archive with information about the structure of crawled content . We add adaptive characteristics to an archival Web crawler : being able to identify when a Web page belongs to a given Web application and applying the appropriate crawling and content extraction methodology .

O B O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O B O O B O O

archiving
crawling
extraction
web application


HyLiEn : a hybrid approach to general list extraction on the web We consider the problem of automatically extracting general lists from the web . Existing approaches are mostly dependent upon either the underlying HTML markup or the visual structure of the Web page . We present HyLiEn an unsupervised , Hybrid approach for automatic List discovery and Extraction on the Web . It employs general assumptions about the visual rendering of lists , and the structural representation of items contained in them . We show that our method significantly outperforms existing methods .

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

web information integration
web lists
web mining


Agent-based semantic web services The Web Services world consists of loosely-coupled distributed systems which adapt to ad-hoc changes by the use of service descriptions that enable opportunistic service discovery . At present , these service descriptions are semantically impoverished , being concerned with describing the functional signature of the services rather than characterising their meaning . In the Semantic Web community , the DAML Services effort attempts to rectify this by providing a more expressive way of describing Web services using ontologies . However , this approach does not separate the domain-neutral communicative intent of a message ( considered in terms of speech acts ) from its domain-specific content , unlike similar developments from the multi-agent systems community . In this paper , we describe our experiences of designing and building an ontologically motivated Web Services system for situational awareness and information triage in a simulated humanitarian aid scenario . In particular , we discuss the merits of using techniques from the multi-agent systems community for separating the intentional force of messages from their content , and the implementation of these techniques within the DAML Services model .

O B I O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O B I O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Scalable integration and processing of linked data The goal of this tutorial is to introduce , motivate and detail techniques for integrating heterogeneous structured data from across the Web . Inspired by the growth in Linked Data publishing , our tutorial aims at educating Web researchers and practitioners about this new publishing paradigm . The tutorial will show how Linked Data enables uniform access , parsing and interpretation of data , and how this novel wealth of structured data can potentially be exploited for creating new applications or enhancing existing ones . As such , the tutorial will focus on Linked Data publishing and related Semantic Web technologies , introducing scalable techniques for crawling , indexing and automatically integrating structured heterogeneous Web data through reasoning .

O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O


Selective hypertext induced topic search We address the problem of answering broad-topic queries on the World Wide Web . We present a link based analysis algorithm SelHITS , which is an improvement over Kleinberg 's HITS ( 2 ) algorithm . We introduce the concept of virtual links to exploit the latent information in the hyperlinked environment . We propose a novel approach to calculate hub and authority values . We also present a selective expansion method which avoids topic drift and provides results consistent with only one interpretation of the query , even if the query is ambiguous . Initial experimental evaluation and user feedback show that our algorithm indeed distills the most important and relevant pages for broad-topic queries . We also infer that there exists a uniform notion of quality of search results within users .

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

link analysis
searching
topic distillation


A messaging API for inter-widgets communication Widget containers are used everywhere on the Web , for instance as customizable start pages to Web desktops . In this poster , we describe the extension of a widget container with an inter-widgets communication layer , as well as the subsequent application programming interfaces ( APIs ) added to the Widget object to support this feature . We present the benefits of a drag and drop facility within widgets and conclude by a call for standardization of inter-widgets communication on the Web .

O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B I I O O O O O O O O O O O O B O O O O


Scaling question answering to the Web


XL : an XML programming language for web service specification and composition We present an XML programming language specially designed for the implementation of Web services . XL is portable and fully compliant with W3C standards such as XQuery , XML Protocol , and XML Schema . One of the key features of XL is that it allows programmers to concentrate on the logic of their application . XL provides high-level and declarative constructs for actions which are typically carried out in the implementation of a Web service ; e.g. , logging , error handling , retry of actions , workload management , events , etc. . Issues such as performance tuning ( e.g. , caching , horizontal partitioning , etc. ) should be carried out automatically by an implementation of the language . This way , the productivity of the programmers , the ability of evolution of the programs , and the chances to achieve good performance are substantially enhanced .

O O O B B I O B I O O O O O O B B I O O O O O O O O O O O O O O O O O O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Rare item detection in e-commerce site As the largest online marketplace in the world , eBay has a huge inventory where there are plenty of great rare items with potentially large , even rapturous buyers . These items are obscured in long tail of eBay item listing and hard to find through existing searching or browsing methods . It is observed that there are great rarity demands from users according to eBay query log . To keep up with the demands , the paper proposes a method to automatically detect rare items in eBay online listing . A large set of features relevant to the task are investigated to filter items and further measure item rareness . The experiments on the most rarity-demand-intensitive domains show that the method may effectively detect rare items ( ) 90 % precision ) .

B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

information search and retrieval
learning
long tail theory
rareness measure


Pushing reactive services to XML repositories using active rules

document management
push technology
query languages for xml
soap
web


Simulation , verification and automated composition of web services Web services -- Web-accessible programs and devices - are a key application area for the Semantic Web . With the proliferation of Web services and the evolution towards the Semantic Web comes the opportunity to automate various Web services tasks . Our objective is to enable markup and automated reasoning technology to describe , simulate , compose , test , and verify compositions of Web services . We take as our starting point the DAML-S DAML+OIL ontology for describing the capabilities of Web services . We define the semantics for a relevant subset of DAML-S in terms of a first-order logical language . With the semantics in hand , we encode our service descriptions in a Petri Net formalism and provide decision procedures for Web service simulation , verification and composition . We also provide an analysis of the complexity of these tasks under different restrictions to the DAML-S composite services we can describe . Finally , we present an implementation of our analysis techniques . This implementation takes as input a DAML-S description of a Web service , automatically generates a Petri Net and performs the desired analysis . Such a tool has broad applicability both as a back end to existing manual Web service composition tools , and as a stand-alone tool for Web service developers .

O O O O O O O B I B I O O O O O O O O O O O O O B I O O O O O B I O O O O O B I O O O O O O B I O O O O O O O O O B I O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O

automated reasoning
semantic web
web service composition
web services

daml
distributed systems
ontologies
representations


Identifying and discriminating between web and peer-to-peer traffic in the network core Traffic classification is the ability to identify and categorize network traffic by application type . In this paper , we consider the problem of traffic classification in the network core . Classification at the core is challenging because only partial information about the flows and their contributors is available . We address this problem by developing a framework that can classify a flow using only unidirectional flow information . We evaluated this approach using recent packet traces that we collected and pre-classified to establish a `` base truth '' . From our evaluation , we find that flow statistics for the server-to-client direction of a TCP connection provide greater classification accuracy than the flow statistics for the client-to-server direction . Because collection of the server-to-client flow statistics may not always be feasible , we developed and validated an algorithm that can estimate the missing statistics froma unidirectional packet trace .

O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

applications
clustering
machine learning


What is Twitter , a social network or a news media ? Twitter , a microblogging service less than three years old , commands more than 41 million users as of July 2009 and is growing fast . Twitter users tweet about any topic within the 140-character limit and follow others to receive their tweets . The goal of this paper is to study the topological characteristics of Twitter and its power as a new medium of information sharing . We have crawled the entire Twitter site and obtained 41.7 million user profiles , 1.47 billion social relations , 4,262 trending topics , and 106 million tweets . In its follower-following topology analysis we have found a non-power-law follower distribution , a short effective diameter , and low reciprocity , which all mark a deviation from known characteristics of human social networks ( 28 ) . In order to identify influentials on Twitter , we have ranked users by the number of followers and by PageRank and found two rankings to be similar . Ranking by retweets differs from the previous two rankings , indicating a gap in influence inferred from the number of followers and that from the popularity of one 's tweets . We have analyzed the tweets of top trending topics and reported on their temporal behavior and user participation . We have classified the trending topics based on the active period and the tweets and show that the majority ( over 85 % ) of topics are headline news or persistent news in nature . A closer look at retweets reveals that any retweeted tweet is to reach an average of 1,000 users no matter what the number of followers is of the original tweet . Once retweeted , a tweet gets retweeted almost instantly on next hops , signifying fast diffusion of information after the 1st retweet . To the best of our knowledge this work is the first quantitative study on the entire Twittersphere and information diffusion on it .

O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B I O O O

information diffusion
pagerank
reciprocity
retweet
twitter

degree of separation
homophily
influential
online social network
social and behavioral sciences


Exploring social dynamics in online media sharing It is now feasible to view media at home as easily as text-based pages were viewed when the World Wide Web ( WWW ) first emerged . This development has supported media sharing and search services providing hosting , indexing and access to large , online media repositories . Many of these sharing services also have a social aspect to them . This paper provides an initial analysis of the social interactions on a video sharing and search service ( www.youtube.com ) . Results show that many users do not form social networks in the online community and a very small number do not appear to contribute to the wider community . However , it does seem those people who do use the available tools have much a greater tendency to form social connections .

O B I O O B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B O O B O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


EP-SPARQL : a unified language for event processing and stream reasoning Streams of events appear increasingly today in various Web applications such as blogs , feeds , sensor data streams , geospatial information , on-line financial data , etc. . Event Processing ( EP ) is concerned with timely detection of compound events within streams of simple events . State-of-the-art EP provides on-the-fly analysis of event streams , but can not combine streams with background knowledge and can not perform reasoning tasks . On the other hand , semantic tools can effectively handle background knowledge and perform reasoning thereon , but can not deal with rapidly changing data provided by event streams . To bridge the gap , we propose Event Processing SPARQL ( EP-SPARQL ) as a new language for complex events and Stream Reasoning . We provide syntax and formal semantics of the language and devise an effective execution model for the proposed formalism . The execution model is grounded on logic programming , and features effective event processing and inferencing capabilities over temporal and static knowledge . We provide an open-source prototype implementation and present a set of tests to show the usefulness and effectiveness of our approach .

O O O O O O O O O O O B O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

complex event processing
etalis
rule systems
semantic web


Transforming web contents into a storybook with dialogues and animations This paper describes a medium , called Interactive e-Hon , for helping children to understand contents from the Web . It works by transforming electronic contents into an easily understandable `` storybook world . '' In this world , easy-to-understand contents are generated by creating 3D animations that include contents and metaphors , and by using a child-parent model with dialogue expression and a question-answering style comprehensible to children .

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O

agent
animation
information presentation
media conversion


METEOR : metadata and instance extraction from object referral lists on the web The Web has established itself as the largest public data repository ever available . Even though the vast majority of information on the Web is formatted to be easily readable by the human eye , `` meaningful information '' is still largely inaccessible for the computer applications . In this paper we present the METEOR system which utilizes various presentation and linkage regularities from referral lists of various sorts to automatically separate and extract metadata and instance information . Experimental results for the university domain with 12 computer science department Web sites , comprising 361 individual faculty and course home pages indicate that the performance of the metadata and instance extraction averages 85 % , 88 % F-measure respectively . METEOR achieves this performance without any domain specific engineering requirement .

O O B O B B O B O O O O B O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B O B B O O O O O O O O O O O O O O O O O O O O


XML query forms ( XQForms ) : declarative specification of XML query interfaces

query forms & reports
web
xml query language
xsl


Less talk , more rock : automated organization of community-contributed collections of concert videos We describe a system for synchronization and organization of user-contributed content from live music events . We start with a set of short video clips taken at a single event by multiple contributors , who were using a varied set of capture devices . Using audio fingerprints , we synchronize these clips such that overlapping clips can be displayed simultaneously . Furthermore , we use the timing and link structure generated by the synchronization algorithm to improve the findability and representation of the event content , including identifying key moments of interest and descriptive text for important captured segments of the show . We also identify the preferred audio track when multiple clips overlap . We thus create a much improved representation of the event that builds on the automatic content match . Our work demonstrates important principles in the use of content analysis techniques for social media content on the Web , and applies those principles in the domain of live music capture .

O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O


Wikipedia vandalism detection Wikipedia is an online encyclopedia that anyone can access and edit . It has become one of the most important sources of knowledge online and many third party projects rely on it for a wide-range of purposes . The open model of Wikipedia allows pranksters , lobbyists and spammers to attack the integrity of the encyclopedia and this endangers it as a public resource . This is known in the community as vandalism . A plethora of methods have been developed within the Wikipedia and the scientific community to tackle this problem . We have participated in this effort and developed one of the leading approaches . Our research aims to create a fully-working antivandalism system and get it working in the real world .

B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

machine learning
natural language processing
reputation


SourceRank : relevance and trust assessment for deep web sources based on inter-source agreement One immediate challenge in searching the deep web databases is source selection - i.e. selecting the most relevant web databases for answering a given query . The existing database selection methods ( both text and relational ) assess the source quality based on the query-similarity-based relevance assessment . When applied to the deep web these methods have two deficiencies . First is that the methods are agnostic to the correctness ( trustworthiness ) of the sources . Secondly , the query based relevance does not consider the importance of the results . These two considerations are essential for the open collections like the deep web . Since a number of sources provide answers to any query , we conjuncture that the agreements between these answers are likely to be helpful in assessing the importance and the trustworthiness of the sources . We compute the agreement between the sources as the agreement of the answers returned . While computing the agreement , we also measure and compensate for possible collusion between the sources . This adjusted agreement is modeled as a graph with sources at the vertices . On this agreement graph , a quality score of a source that we call SourceRank , is calculated as the stationary visit probability of a random walk . We evaluate SourceRank in multiple domains , including sources in Google Base , with sizes up to 675 sources . We demonstrate that the SourceRank tracks source corruption . Further , our relevance evaluations show that SourceRank improves precision by 22-60 % over the Google Base and the other baseline methods . SourceRank has been implemented in a system called Factal .

B O O O O O O B I O O O O O O O O O O O B I O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O


2lip : the step towards the web3d The World Wide Web allows users to create and publish a variety of resources , including multimedia ones . Most of the contemporary best practices for designing web interfaces , however , do not take into account the 3D techniques . In this paper we present a novel approach for designing interactive web applications -- 2-Layer Interface Paradigm ( 2LIP ) . The background layer of the 2LIP-type user interface is a 3D scene , which a user can not directly interact with . The foreground layer is HTML content . Only taking an action on this content ( e.g. pressing a hyperlink , scrolling a page ) can affect the 3D scene . We introduce a reference implementation of 2LIP : Copernicus - The Virtual 3D Encyclopedia , which shows one of the potential paths of the evolution of Wikipedia towards Web 3.0 . Based on the evaluation of Copernicus we prove that designing web interfaces according to 2LIP provides users a better browsing experience , without harming the interaction .

O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


A convenient method for securely managing passwords Computer users are asked to generate , keep secret , and recall an increasing number of passwords for uses including host accounts , email servers , e-commerce sites , and online financial services . Unfortunately , the password entropy that users can comfortably memorize seems insufficient to store unique , secure passwords for all these accounts , and it is likely to remain constant as the number of passwords ( and the adversary 's computational power ) increases into the future . In this paper , we propose a technique that uses a strengthened cryptographic hash function to compute secure passwords for arbitrarily many accounts while requiring the user to memorize only a single short password . This mechanism functions entirely on the client ; no server-side changes are needed . Unlike previous approaches , our design is both highly resistant to brute force attacks and nearly stateless , allowing users to retrieve their passwords from any location so long as they can execute our program and remember a short secret . This combination of security and convenience will , we believe , entice users to adopt our scheme . We discuss the construction of our algorithm in detail , compare its strengths and weaknesses to those of related approaches , and present Password Multiplier , an implementation in the form of an extension to the Mozilla Firefox web browser .

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

password security
website user authentication


Automatic generation of web portals using artificial ants We present in this work a new model ( named AntTree ) based on artificial ants for document hierarchical clustering . This model is inspired from the self-assembly behavior of real ants . We have simulated this behavior to build a hierarchical tree-structured partitioning of a set of documents , according to the similarities between these documents . We have successfully compared our results to those obtained by ascending hierarchical clustering .

O O O B O O B I O O O O O O O O O O O O O O B I O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O

artificial ants
hierarchical clustering
web


On admission control for profit maximization of networked service providers Variability and diverseness among incoming requests to a service hosted on a finite capacity resource necessitates sophisticated request admission control techniques for providing guaranteed quality of service ( QoS ) . We propose in this paper a service time based online admission control methodology for maximizing profits of a service provider . The proposed methodology chooses a subset of incoming requests such that the revenue of the provider is maximized . Admission control decision in our proposed system is based upon an estimate of the service time of the request , QoS bounds , prediction of arrivals and service times of requests to come in the short-term future , and rewards associated with servicing a request within its QoS bounds . Effectiveness of the proposed admission control methodology is demonstrated using experiments with a content-based messaging middleware service .

O B I O B I O O O O O O O O O O O O O O O O O O O O O O B I O O O O B I I O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O

admission control
profit maximization
quality of service

performance of systems
service level agreement
service time estimation
short-term prediction
shortest remaining job first
web service


Design and implementation of a feedback controller for slowdown differentiation on internet servers Proportional slowdown differentiation ( PSD ) aims to maintain slowdown ratios between different classes of clients according to their pre-specified differentiation parameters . In this paper , we design a feedback controller to allocate processing rate on Internet servers for PSD . In this approach , the processing rate of a class is adjusted by an integral feedback controller according to the difference between the target slowdown ratio and the achieved one . The initial rate class is estimated based on predicted workload using queueing theory . We implement the feedback controller in an Apache Web server . The experimental results under various environments demonstrate the controller 's effectiveness and robustness .

O O O O O O O O B O O O O O B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

feedback control
performance of systems
quality of service


Hybrid multicasting in large-scale service networks The importance of service composition has been widely recognized in the Internet research community due to its high flexibility in allowing development of customized applications . So far little attention has been paid to composite services ' runtime performance-related aspects , which are of great importance to wide-area applications . Service composition in the wide area actually creates a new type of routing problem which we call QoS service routing . We study this problem in large networks ( e.g. , the Web ) and provide distributed and scalable routing solutions with various optimization goals . Most importantly , we propose ways to reduce redundancies of data delivery and service execution through explorations of different types of multicast ( service multicast and data multicast ) in one-to-many application scenarios .

O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B O O B O O O O O O


Bringing communities to the semantic web and the semantic web to communities In this paper we consider the types of community networks that are most often codified within the Semantic Web . We propose the recognition of a new structure which fulfils the definition of community used outside the Semantic Web . We argue that the properties inherent in a community allow additional processing to be done with the described relationships existing between entities within the community network . Taking an existing online community as a case study we describe the ontologies and applications that we developed to support this community in the Semantic Web environment and discuss what lessons can be learned from this exercise and applied in more general settings .

O B O O B I O O B I O B O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O

e-applications
group and organization interfaces


Traffic characterization and internet usage in rural Africa While Internet connectivity has reached a significant part of the world 's population , those living in rural areas of the developing world are still largely disconnected . Recent efforts have provided Internet connectivity to a growing number of remote locations , yet Internet traffic demands cause many of these networks to fail to deliver basic quality of service needed for simple applications . For an in-depth investigation of the problem , we gather and analyze network traces from a rural wireless network in Macha , Zambia . We supplement our analysis with on-site interviews from Macha , Zambia and Dwesa , South Africa , another rural community that hosts a local wireless network . The results reveal that Internet traffic in rural Africa differs significantly from the developed world . We observe dominance of web-based traffic , as opposed to peer-to-peer traffic common in urban areas . Application-wise , online social networks are the most popular , while the majority of bandwidth is consumed by large operating system updates . Our analysis also uncovers numerous network anomalies , such as significant malware traffic . Finally , we find a strong feedback loop between network performance and user behavior . Based on our findings , we conclude with a discussion of new directions in network design that take into account both technical and social factors .

O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Using graphics processors for high performance IR query processing Web search engines are facing formidable performance challenges due to data sizes and query loads . The major engines have to process tens of thousands of queries per second over tens of billions of documents . To deal with this heavy workload , such engines employ massively parallel systems consisting of thousands of machines . The significant cost of operating these systems has motivated a lot of recent research into more efficient query processing mechanisms . We investigate a new way to build such high performance IR systems using graphical processing units ( GPUs ) . GPUs were originally designed to accelerate computer graphics applications through massive on-chip parallelism . Recently a number of researchers have studied how to use GPUs for other problem domains such as databases and scientific computing . Our contribution here is to design a basic system architecture for GPU-based high-performance IR , to develop suitable algorithms for subtasks such as inverted list compression , list intersection , and top - $ k $ scoring , and to show how to achieve highly efficient query processing on GPU-based systems . Our experimental results for a prototype GPU-based system on $ 25.2 $ million web pages indicate that significant gains in query processing performance can be obtained .

O O O O O O B I I O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

gpu
index compression
information search and retrieval


BizCQ : using continual queries to cope with changes in business information exchange In this poster , we propose the framework of BizCQ , a system to apply Continual Queries ( 7 ) ( 8 ) on Web-based content to manage information exchanges between two business partners . In this poster , we describe ways to leverage previous research in Web monitoring techniques applied to the everyday problem of managing change within a business environment , and focus on the difficulties of managing changes that are caused by external parties in business-to-business ( B2B ) information exchanges .

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O

business-to-business
change response
content analysis and indexing
continual query
information quality
semantic web


Using proximity to predict activity in social networks The structure of a social network contains information useful for predicting its evolution . We show that structural information also helps predict activity . People who are `` close '' in some sense in a social network are more likely to perform similar actions than more distant people . We use network proximity to capture the degree to which people are `` close '' to each other . In addition to standard proximity metrics used in the link prediction task , such as neighborhood overlap , we introduce new metrics that model different types of interactions that take place between people . We study this claim empirically using data about URL forwarding activity on the social media sites Digg and Twitter . We show that structural proximity of two users in the follower graph is related to similarity of their activity , i.e. , how many URLs they both forward . We also show that given friends ' activity , knowing their proximity to the user can help better predict which URLs the user will forward . We compare the performance of different proximity metrics on the activity prediction task and find that metrics that take into account the attention-limited nature of interactions in social media lead to substantially better predictions .

O B O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O B I O O O O O O O O O O O O O O O B I O O O O O O

activity prediction
proximity
social media
social networks


Buy-it-now or take-a-chance : a simple sequential screening mechanism We present a simple auction mechanism which extends the second-price auction with reserve and is truthful in expectation . This mechanism is particularly effective in private value environments where the distribution of valuations are irregular . Bidders can `` buy-it-now '' , or alternatively `` take-a-chance '' where the top d bidders are equally likely to win . The randomized take-a-chance allocation incentivizes high valuation bidders to buy-it-now . We show that for a large class of valuations , this mechanism achieves similar allocations and revenues as Myerson 's optimal mechanism , and outperforms the second-price auction with reserve . In addition , we present an evaluation of bid data from Microsoft 's AdECN platform . We find the valuations are irregular , and counterfactual experiments suggest our BIN-TAC mechanism would improve revenue by 11 % relative to an optimal second-price mechanism with reserve .

O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

ad auctions
electronic commerce
mechanism design
online advertising


Filtering microblogging messages for social tv Social TV was named one of the ten most important emerging technologies in 2010 by the MIT Technology Review . Manufacturers of set-top boxes and televisions have recently started to integrate access to social networks into their products . Some of these systems allow users to read microblogging messages related to the TV program they are currently watching . However , such systems suffer from low precision and recall when they use the title of the show as keywords when retrieving messages , without any additional filtering . We propose a bootstrapping approach to collecting microblogging messages related to a given TV program . We start with a small set of annotated data , in which , for a given show and a candidate message , we annotate the pair to be relevant or irrelevant . From this annotated data set , we train an initial classifier . The features are designed to capture the association between the TV program and the message . Using our initial classifier and a large dataset of unlabeled messages we derive broader features for a second classifier to further improve precision .

B B O O B I B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


A clustering method for web data with multi-type interrelated components Traditional clustering algorithms work on `` flat '' data , making the assumption that the data instances can only be represented by a set of homogeneous and uniform features . Many real world data , however , is heterogeneous in nature , comprising of multiple types of interrelated components . We present a clustering algorithm , K-SVMeans , that integrates the well known K-Means clustering with the highly popular Support Vector Machines ( SVM ) in order to utilize the richness of data . Our experimental results on authorship analysis of scientific publications show that K-SVMeans achieves better clustering performance than homogeneous data clustering .

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

k-means
k-svmeans
multi-type data clustering
online svm


Newsjunkie : providing personalized newsfeeds via analysis of information novelty We present a principled methodology for filtering news stories by formal measures of information novelty , and show how the techniques can be usedto custom-tailor news feeds based on information that a user has already reviewed . We review methods for analyzing novelty and then describe Newsjunkie , a system that personalizes news for users by identifying the novelty of stories in the context of stories they have already reviewed . Newsjunkie employs novelty-analysis algorithms that represent articles as words and named entities . The algorithms analyze inter-andintra-document dynamics by considering how information evolves over timefrom article to article , as well as within individual articles . We review the results of a user study undertaken to gauge the value of the approachover legacy time-based review of newsfeeds , and also to compare the performance of alternate distance metrics that are used to estimate the dissimilarity between candidate new articles and sets of previously reviewed articles .

O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Framework and algorithms for network bucket testing Bucket testing , also known as split testing , A\/B testing , or 0\/1 testing , is a widely used method for evaluating users ' satisfaction with new features , products , or services . In order not to expose the whole user base to the new service , the mean user satisfaction rate is estimated by exposing the service only to a few uniformly chosen random users . In a recent work , Backstrom and Kleinberg , defined the notion of network bucket testing for social services . In this context , users ' interactions are only valid for measurement if some minimal number of their friends are also given the service . The goal is to estimate the mean user satisfaction rate while providing the service to the least number of users . This constraint makes uniform sampling , which is optimal for the traditional case , grossly inefficient . In this paper we introduce a simple general framework for designing and evaluating sampling techniques for network bucket testing . The framework is constructed in a way that sampling algorithms are only required to generate sets of users to which the service should be provided . Given an algorithm , the framework produces an unbiased user satisfaction rate estimator and a corresponding variance bound for any network and any user satisfaction function . Furthermore , we present several simple sampling algorithms that are evaluated using both synthetic and real social networks . Our experiments corroborate the theoretical results and demonstrate the effectiveness of the proposed framework and algorithms .

O O O O O B I B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O

a/b testing
network bucket testing
nonnumerical algorithms and problems


A personalized search engine based on web-snippet hierarchical clustering In this paper we propose a hierarchical clustering engine , called snaket , that is able to organize on-the-fly the search results drawn from 16 commodity search engines into a hierarchy of labeled folders . The hierarchy offers a complementary view to the flat-ranked list of results returned by current search engines . Users can navigate through the hierarchy driven by their search needs . This is especially useful for informative , polysemous and poor queries . SnakeT is the first complete and open-source system in the literature that offers both hierarchical clustering and folder labeling with variable-length sentences . We extensively test SnakeT against all available web-snippet clustering engines , and show that it achieves efficiency and efficacy performance close to the best known engine Vivisimo.com . Recently , personalized search engines have been introduced with the aim of improving search results by focusing on the users , rather than on their submitted queries . We show how to plug SnakeT on top of any ( un-personalized ) search engine in order to obtain a form of personalization that is fully adaptive , privacy preserving , scalable , and non intrusive for underlying search engines .

O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O

content analysis and indexing
information extraction
information search and retrieval
new search applications and interfaces
on-line information services
personalized web ranking
web snippets clustering


A web services architecture for learning object discovery and assembly Courseware systems are often based on an assembly of different components , addressing the different needs of storage and delivery functionality . The Learning Technology Standard Architecture LTSA provides a generic architectural framework for these systems . Recent developments in Web technology -- e.g. the Web services framework -- have greatly enhanced the flexible and interoperable implementation of courseware architectures . We argue that in order to make the Web services philosophy work , two enhancements to the LTSA approach are required . Firstly , a combination with metadata annotation is needed to support the discovery of educational Web services . Secondly , if these components are to be provided in form of services , more support is needed for their assembly . Architectural patterns of a finer degree of granularity shall satisfy this need .

O B I B O O O B O B O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O B O O O O O O B O O B I O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O

architecture
assembly
discovery
metadata
web services

interface descriptions
teaching and learning environments


Trust analysis with clustering Web provides rich information about a variety of objects . Trustability is a major concern on the web . Truth establishment is an important task so as to provide the right information to the user from the most trustworthy source . Trustworthiness of information provider and the confidence of the facts it provides are inter-dependent on each other and hence can be expressed iteratively in terms of each other . However , a single information provider may not be the most trustworthy for all kinds of information . Every information provider has its own area of competence where it can perform better than others . We derive a model that can evaluate trustability on objects and information providers based on clusters ( groups ) . We propose a method which groups the set of objects for which similar set of providers provide `` good '' facts , and provides better accuracy in addition to high quality object clusters .

B O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O