Web 2.0 : blind to an accessible new world With the advent of Web 2.0 technologies , websites have evolved from static pages to dynamic , interactive Web-based applications with the ability to replicate common desktop functionality . However , for blind and visually impaired individuals who rely upon screen readers , Web 2.0 applications force them to adapt to an inaccessible use model . Many technologies , including WAI-ARIA , AJAX , and improved screen reader support , are rapidly evolving to improve this situation . However , simply combining them does not solve the problems of screen reader users . The main contributions of this paper are two models of interaction for screen reader users , for both traditional websites and Web 2.0 applications . Further contributions are a discussion of accessibility difficulties screen reader users encounter when interacting with Web 2.0 applications , a user workflow design model for improving Web 2.0 accessibility , and a set of design requirements for developers to ease the user 's burden and increase accessibility . These models , accessibility difficulties , and design implications are based directly on responses and lessons learned from usability research focusing on Web 2.0 usage and screen reader users . Without the conscious effort of Web engineers and designers , most blind and visually impaired users will shy away from using new Web 2.0 technology in favor of desktop based applications .

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


Cyclone : an encyclopedic web search site We propose a Web search site called `` Cyclone '' , in which a user can retrieve encyclopedic term descriptions on the Web . Cyclone searches the Web for headwords and page fragments describing the headwords . High-quality page fragments are selected as term descriptions and are classified into domains . The number of current headwords is over 700,000 .

O O O O 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 O O O O O O

encyclopedias
extraction
information search and retrieval
natural language processing
on-line information services
organization


Towards a highly-scalable and effective metasearch engine

database selection
distributed text database
resource discovery


Spotting fake reviewer groups in consumer reviews Opinionated social media such as product reviews are now widely used by individuals and organizations for their decision making . However , due to the reason of profit or fame , people try to game the system by opinion spamming ( e.g. , writing fake reviews ) to promote or demote some target products . For reviews to reflect genuine user experiences and opinions , such spam reviews should be detected . Prior works on opinion spam focused on detecting fake reviews and individual fake reviewers . However , a fake reviewer group ( a group of reviewers who work collaboratively to write fake reviews ) is even more damaging as they can take total control of the sentiment on the target product due to its size . This paper studies spam detection in the collaborative setting , i.e. , to discover fake reviewer groups . The proposed method first uses a frequent itemset mining method to find a set of candidate groups . It then uses several behavioral models derived from the collusion phenomenon among fake reviewers and relation models based on the relationships among groups , individual reviewers , and products they reviewed to detect fake reviewer groups . Additionally , we also built a labeled dataset of fake reviewer groups . Although labeling individual fake reviews and reviewers is very hard , to our surprise labeling fake reviewer groups is much easier . We also note that the proposed technique departs from the traditional supervised learning approach for spam detection because of the inherent nature of our problem which makes the classic supervised learning approach less effective . Experimental results show that the proposed method outperforms multiple strong baselines including the state-of-the-art supervised classification , regression , and learning to rank 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 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

fake review detection
group opinion spam
social and behavioral sciences


Communities from seed sets Expanding a seed set into a larger community is a common procedure in link-based analysis . We show how to adapt recent results from theoretical computer science to expand a seed set into a community with small conductance and a strong relationship to the seed , while examining only a small neighborhood of the entire graph . We extend existing results to give theoretical guarantees that apply to a variety of seed sets from specified communities . We also describe simple and flexible heuristics for applying these methods in practice , and present early experiments showing that these methods compare favorably with existing approaches .

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 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

community finding
graph conductance
link analysis
random walks


sMash : semantic-based mashup navigation for data API network With the proliferation of data APIs , it is not uncommon that users who have no clear ideas about data APIs will encounter difficulties to build Mashups to satisfy their requirements . In this paper , we present a semantic-based mashup navigation system , sMash that makes mashup building easy by constructing and visualizing a real-life data API network . We build a sample network by gathering more than 300 popular APIs and find that the relationships between them are so complex that our system will play an important role in navigating users and give them inspiration to build interesting mashups easily . The system is accessible at : http:\/\/www.dart.zju.edu.cn\/mashup .

O O O B I 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 B I 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


Parallel boosted regression trees for web search ranking Gradient Boosted Regression Trees ( GBRT ) are the current state-of-the-art learning paradigm for machine learned web-search ranking - a domain notorious for very large data sets . In this paper , we propose a novel method for parallelizing the training of GBRT . Our technique parallelizes the construction of the individual regression trees and operates using the master-worker paradigm as follows . The data are partitioned among the workers . At each iteration , the worker summarizes its data-partition using histograms . The master processor uses these to build one layer of a regression tree , and then sends this layer to the workers , allowing the workers to build histograms for the next layer . Our algorithm carefully orchestrates overlap between communication and computation to achieve good performance . Since this approach is based on data partitioning , and requires a small amount of communication , it generalizes to distributed and shared memory machines , as well as clouds . We present experimental results on both shared memory machines and clusters for two large scale web search ranking data sets . We demonstrate that the loss in accuracy induced due to the histogram approximation in the regression tree creation can be compensated for through slightly deeper trees . As a result , we see no significant loss in accuracy on the Yahoo data sets and a very small reduction in accuracy for the Microsoft LETOR data . In addition , on shared memory machines , we obtain almost perfect linear speed-up with up to about 48 cores on the large data sets . On distributed memory machines , we get a speedup of 25 with 32 processors . Due to data partitioning our approach can scale to even larger data sets , on which one can reasonably expect even higher speedups .

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

boosted regression trees
ranking
web search

boosting
distributed computing
general
machine learning
parallel computing


Information flow modeling based on diffusion rate for prediction and ranking Information flows in a network where individuals influence each other . The diffusion rate captures how efficiently the information can diffuse among the users in the network . We propose an information flow model that leverages diffusion rates for : ( 1 ) prediction . identify where information should flow to , and ( 2 ) ranking . identify who will most quickly receive the information . For prediction , we measure how likely information will propagate from a specific sender to a specific receiver during a certain time period . Accordingly a rate-based recommendation algorithm is proposed that predicts who will most likely receive the information during a limited time period . For ranking , we estimate the expected time for information diffusion to reach a specific user in a network . Subsequently , a DiffusionRank algorithm is proposed that ranks users based on how quickly information will flow to them . Experiments on two datasets demonstrate the effectiveness of the proposed algorithms to both improve the recommendation performance and rank users by the efficiency of information flow .

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

collaborative filtering
continuous-time markov chain
diffusion of innovation
social influence
web ranking


Ontology-based learning content repurposing This paper investigates basic research issues that need to be addressed for developing an architecture that enables repurposing of learning objects in a flexible way . Currently , there are a number of Learning Object Content Models ( e.g. the SCORM Content Aggregation Model ) that define learning objects and their components in a more or less precise way . However , these models do not allow repurposing of fine-grained components ( sentences , images ) . We developed an ontology-based solution for content repurposing . The ontology is a solid basis for an architecture that will enable on-the-fly access to learning object components and that will facilitate repurposing these components .

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

content models
learning objects
repurposing


Open user profiles for adaptive news systems : help or harm ? Over the last five years , a range of projects have focused on progressively more elaborated techniques for adaptive news delivery . However , the adaptation process in these systems has become more complicated and thus less transparent to the users . In this paper , we concentrate on the application of open user models in adding transparency and controllability to adaptive news systems . We present a personalized news system , YourNews , which allows users to view and edit their interest profiles , and report a user study on the system . Our results confirm that users prefer transparency and control in their systems , and generate more trust to such systems . However , similar to previous studies , our study demonstrate that this ability to edit user profiles may also harm the system . s performance and has to be used with caution .

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

news personalization
open user model
user profile


Hera presentation generator Semantic Web Information Systems ( SWIS ) are Web Information Systems that use Semantic Web technologies . Hera is a model-driven design methodology for SWIS . In Hera , models are represented in RDFS and model instances in RDF . The Hera Presentation Generator ( HPG ) is an integrated development environment that supports the presentation generation layer of the Hera methodology . The HPG is based on a pipeline of data transformations driven by different Hera models .

O O O B I O O O B 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 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

computer-aided software engineering
design environment
wis


To randomize or not to randomize : space optimal summaries for hyperlink analysis Personalized PageRank expresses link-based page quality around user selected pages . The only previous personalized PageRank algorithm that can serve on-line queries for an unrestricted choice of pages on large graphs is our Monte Carlo algorithm ( WAW 2004 ) . In this paper we achieve unrestricted personalization by combining rounding and randomized sketching techniques in the dynamic programming algorithm of Jeh and Widom ( WWW 2003 ) . We evaluate the precision of approximation experimentally on large scale real-world data and find significant improvement over previous results . As a key theoretical contribution we show that our algorithms use an optimal amount of space by also improving earlier asymptotic worst-case lower bounds . Our lower bounds and algorithms apply to the SimRank as well ; of independent interest is the reduction of the SimRank computation to personalized PageRank .

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 streams
information search and retrieval
link-analysis
probabilistic algorithms
scalability
similarity search


Executing incoherency bounded continuous queries at web data aggregators Continuous queries are used to monitor changes to time varying data and to provide results useful for online decision making . Typically a user desires to obtain the value of some function over distributed data items , for example , to determine when and whether ( a ) the traffic entering a highway from multiple feed roads will result in congestion in a thoroughfare or ( b ) the value of a stock portfolio exceeds a threshold . Using the standard Web infrastructure for these applications will increase the reach of the underlying information . But , since these queries involve data from multiple sources , with sources supporting standard HTTP ( pull-based ) interfaces , special query processing techniques are needed . Also , these applications often have the flexibility to tolerate some incoherency , i.e. , some differences between the results reported to the user and that produced from the virtual database made up of the distributed data sources . In this paper , we develop and evaluate client-pull-based techniques for refreshing data so that the results of the queries over distributed data can be correctly reported , conforming to the limited incoherency acceptable to the users . We model as well as estimate the dynamics of the data items using a probabilistic approach based on Markov Chains . Depending on the dynamics of data we adapt the data refresh times to deliver query results with the desired coherency . The commonality of data needs of multiple queries is exploited to further reduce refresh overheads . Effectiveness of our approach is demonstrated using live sources of dynamic data : the number of refreshes it requires is ( a ) an order of magnitude less than what we would need if every potential update is pulled from the sources , and ( b ) comparable to the number of messages needed by an ideal algorithm , one that knows how to optimally refresh the data from distributed data sources . Our evaluations also bring out a very practical and attractive tradeoff property of pull based approaches , e.g. , a small increase in tolerable incoherency leads to a large decrease in message overheads .

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

coherency
continuous queries
online decision making


GigaHash : scalable minimal perfect hashing for billions of urls A minimal perfect function maps a static set of n keys on to the range of integers { 0,1,2 , ... , n - 1 } . We present a scalable high performance algorithm based on random graphs for constructing minimal perfect hash functions ( MPHFs ) . For a set of n keys , our algorithm outputs a description of h in expected time O ( n ) . The evaluation of h ( x ) requires three memory accesses for any key x and the description of h takes up 0.89 n bytes ( 7.13 n bits ) . This is the best ( most space efficient ) known result to date . Using a simple heuristic and Huffman coding , the space requirement is further reduced to 0.79 n bytes ( 6.86 n bits ) . We present a high performance architecture that is easy to parallelize and scales well to very large data sets encountered in internet search applications . Experimental results on a one billion URL dataset obtained from Live Search crawl data , show that the proposed algorithm ( a ) finds an MPHF for one billion URLs in less than 4 minutes , and ( b ) requires only 6.86 bits\/key for the description of h.

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

perfect hash function
space efficient hash table
web search engine


Web mashup scripting language The Web Mashup Scripting Language ( WMSL ) enables an end-user ( you ) working from his browser , e.g. not needing any other infrastructure , to quickly write mashups that integrate any two , or more , web services on the Web . The end-user accomplishes this by writing a web page that combines HTML , metadata in the form of mapping relations , and small piece of code , or script . The mapping relations enable not only the discovery and retrieval of the WMSL pages , but also affect a new programming paradigm that abstracts many programming complexities from the script writer . Furthermore , the WMSL Web pages or scripts that disparate end-users ( you ) write , can be harvested by Crawlers to automatically generate the concepts needed to build lightweight ontologies containing local semantics of a web service and its data model , to extend context ontologies or middle ontologies , and to develop links , or mappings , between these ontologies . This enables an open-source model of building ontologies based on the WMSL Web page or scripts that end users ( you ) write .

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

html
ontologies
scripts
semantics
web services


Hybrid semantic tagging for information extraction The semantic web is expected to have an impact at least as big as that of the existing HTML based web , if not greater . However , the challenge lays in creating this semantic web and in converting existing web information into the semantic paradigm . One of the core technologies that can help in migration process is automatic markup , the semantic markup of content , providing the semantic tags to describe the raw content . This paper describes a hybrid statistical and knowledge-based information extraction model , able to extract entities and relations at the sentence level . The model attempts to retain and improve the high accuracy levels of knowledge-based systems while drastically reducing the amount of manual labor by relying on statistics drawn from a training corpus . The implementation of the model , called TEG ( Trainable Extraction Grammar ) , can be adapted to any IE domain by writing a suitable set of rules in a SCFG ( Stochastic Context Free Grammar ) based extraction language , and training them using an annotated corpus . The experiments show that our hybrid approach outperforms both purely statistical and purely knowledge-based systems , while requiring orders of magnitude less manual rule writing and smaller amount of training data . We also demonstrate the robustness of our system under conditions of poor training data quality . This makes the system very suitable for converting legacy web pages to semantic web pages .

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 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 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 B I O O

content analysis and indexing
hmm
learning
rules based systems
text mining


Estimating required recall for successful knowledge acquisition from the web Information on the Web is not only abundant but also redundant . This redundancy of information has an important consequence on the relation between the recall of an information gathering system and its capacity to harvest the core information of a certain domain of knowledge . This paper provides a new idea for estimating the necessary Web coverage of a knowledge acquisition system in order to achieve a certain desired coverage of the contained core information .

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 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

information extraction
information search and retrieval
quantitative performance measures
web metrics


Just the right amount : extracting modules from ontologies The ability to extract meaningful fragments from an ontology is key for ontology re-use . We propose a definition of a module that guarantees to completely capture the meaning of a given set of terms , i.e. , to include all axioms relevant to the meaning of these terms , and study the problem of extracting minimal modules . We show that the problem of determining whether a subset of an ontology is a module for a given vocabulary is undecidable even for rather restricted sub-languages of OWL DL . Hence we propose two `` approximations '' , i.e. , alternative definitions of modules for a vocabulary that still provide the above guarantee , but that are possibly too strict , and that may thus result in larger modules : the first approximation is semantic and can be computed using existing DL reasoners ; the second is syntactic , and can be computed in polynomial time . Finally , we report on an empirical evaluation of our syntactic approximation which demonstrates that the modules we extract are surprisingly small .

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 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

knowledge representation formalisms and methods


Dataplorer : a scalable search engine for the data web More and more structured information in the form of semantic data is nowadays available . It offers a wide range of new possibilities especially for semantic search and Web data integration . However , their effective exploitation still brings about a number of challenges , e.g. usability , scalability and uncertainty . In this paper , we present Dataplorer , a solution designed to address these challenges . We consider the usability through the use of hybrid queries and faceted search , while still preserving the scalability thanks to an extension of inverted index to support this type of query . Moreover , Dataplorer deals with uncertainty by means of a powerful ranking scheme to find relevant results . Our experimental results show that our proposed approach is promising and it makes us believe that it is possible to extend the current IR infrastructure to query and search the Web of data .

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

hybrid query
information search and retrieval


Visualization of Geo-annotated pictures in mobile phones In this work , a novel mobile browser for geo-referenced pictures is introduced and described . We use the term browser to denote a system aimed at browsing pictures selected from a large set like Internet photo sharing services . The criteria to filter a subset of pictures to browse are three : the user 's actual position , the user 's actual heading , and the user 's preferences . In this work we only focus on the first two criteria leaving the integration of user 's preferences for future developments .

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

arduino
compass
geo-browsing
gps
interaction styles
maps
mobile photo browsing


Scholarly publishing and argument in hyperspace The World Wide Web is opening up access to documents and data for scholars . However it has not yet impacted on one of the primary activities in research : assessing new findings in the light of current knowledge and debating it with colleagues . The ClaiMaker system uses a directed graph model with similarities to hypertext , in which new ideas are published as nodes , which other contributors can build on or challenge in a variety of ways by linking to them . Nodes and links have semantic structure to facilitate the provision of specialist services for interrogating and visualizing the emerging network . By way of example , this paper is grounded in a ClaiMaker model to illustrate how new claims can be described in this structured way .

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 web
digital libraries
hypertext/hypermedia
modeling debate
scholarly interpretation
scientific publishing


Improving mobile internet usability


Improving text collection selection with coverage and overlap statistics In an environment of distributed text collections , the first step in the information retrieval process is to identify which of all available collections are more relevant to a given query and which should thus be accessed to answer the query . We address the challenge of collection selection when there is full or partial overlap between the available text collections , a scenario which has not been examined previously despite its real-world applications . To that end , we present COSCO , a collection selection approach which uses collection-specific coverage and overlap statistics . We describe our experimental results which show that the presented approach displays the desired behavior of retrieving more new results early on in the collection order , and performs consistently and significantly better than CORI , previously considered to be one of the best collection selection systems .

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 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 B I O O


Distributed cooperative Apache web server

dc-apache
distributed web server
load balancing
replication
scalable web server
servers
www


Threshold selection for web-page classification with highly skewed class distribution We propose a novel cost-efficient approach to threshold selection for binary web-page classification problems with imbalanced class distributions . In many binary-classification tasks the distribution of classes is highly skewed . In such problems , using uniform random sampling in constructing sample sets for threshold setting requires large sample sizes in order to include a statistically sufficient number of examples of the minority class . On the other hand , manually labeling examples is expensive and budgetary considerations require that the size of sample sets be limited . These conflicting requirements make threshold selection a challenging problem . Our method of sample-set construction is a novel approach based on stratified sampling , in which manually labeled examples are expanded to reflect the true class distribution of the web-page population . Our experimental results show that using false positive rate as the criterion for threshold setting results in lower-variance threshold estimates than using other widely used accuracy measures such as F1 and precision .

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

skewed class distribution
stratified sampling
threshold selection

binary classifier
miscellaneous
web-page classification


Wake-on-WLAN In bridging the digital divide , two important criteria are cost-effectiveness , and power optimization . While 802.11 is cost-effective and is being used in several installations in the developing world , typical system configurations are not really power efficient . In this paper , we propose a novel `` Wake-on-WLAN '' mechanism for coarse-grained , on-demand power on\/off of the networking equipment at a remote site . The novelty also lies in our implementation of a prototype system using low-power 802.15.4-based sensor motes . We describe the prototype , as well as its evaluation on field in a WiFi testbed . Preliminary estimates indicate that the proposed mechanism can save significant power in typical rural networking settings .

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

802.11 mesh network
802.15.4
network architecture and design
power management
wake-on-wlan


Rapid prototyping of semantic mash-ups through semantic web pipes The use of RDF data published on the Web for applications is still a cumbersome and resource-intensive task due to the limited software support and the lack of standard programming paradigms to deal with everyday problems such as combination of RDF data from dierent sources , object identifier consolidation , ontology alignment and mediation , or plain querying and filtering tasks . In this paper we present a framework , Semantic Web Pipes , that supports fast implementation of Semantic data mash-ups while preserving desirable properties such as abstraction , encapsulation , component-orientation , code re-usability and maintainability which are common and well supported in other application areas .

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


Modeling user behavior in recommender systems based on maximum entropy We propose a model for user purchase behavior in online stores that provide recommendation services . We model the purchase probability given recommendations for each user based on the maximum entropy principle using features that deal with recommendations and user interests . The proposed model enable us to measure the effect of recommendations on user purchase behavior , and the effect can be used to evaluate recommender systems . We show the validity of our model using the log data of an online cartoon distribution service , and measure the recommendation effects for evaluating the recommender system .

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 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 B O O O O O O O

maximum entropy principle
recommendation


Dtwiki : a disconnection and intermittency tolerant wiki Wikis have proven to be a valuable tool for collaboration and content generation on the web . Simple semantics and ease-of-use make wiki systems well suited for meeting many emerging region needs in the areas of education , collaboration and local content generation . Despite their usefulness , current wiki software does not work well in the network environments found in emerging regions . For example , it is common to have long-lasting network partitions due to cost , power and poor connectivity . Network partitions make a traditional centralized wiki architecture unusable due to the unavailability of the central server . Existing solutions towards addressing connectivity problems include web-caching proxies and snapshot distribution . While proxies and snapshots allow wiki data to be read while disconnected , they prevent users from contributing updates back to the wiki . In this paper we detail the design and implementation of DTWiki , a wiki system which explicitly addresses the problem of operating a wiki system in an intermittent environment . The DTWiki system is able to cope with long-lasting partitions and bad connectivity while providing the functionality of popular wiki software such as MediaWiki and TWiki .

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 O O 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 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 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

delay-tolerant networking
developing regions
general


GeoTV : navigating geocoded rss to create an iptv experience The Web is rapidly moving towards a platform for mass collaboration in content production and consumption from three screens : computers , mobile phones , and TVs . While there has been a surge of interests in making Web content accessible from mobile devices , there is a significant lack of progress when it comes to making the web experience suitable for viewing on a television . Towards this end , we describe a novel concept , namely GeoTV , where we explore a framework by which web content can be presented or pushed in a meaningful manner to create an entertainment experience for the TV audience . Fresh content on a variety of topics , people , and places is being created and made available on the Web at breathtaking speed . Navigating fresh content effectively on TV demands a new browsing paradigm that requires fewer mouse clicks or user interactions from the remote control . Novel geospatial and temporal browsing techniques are provided in GeoTV that allow users the capability of aggregating and navigating RSS-enabled content in a timely , personalized and automatic manner for viewing in an IPTV environment . This poster is an extension of our previous work on GeoTracker that utilizes both a geospatial representation and a temporal ( chronological ) presentation to help users spot the most relevant updates quickly within the context of a Web-enabled environment . We demonstrate 1 ) the usability of such a tool that greatly enhances a user . s ability in locating and browsing videos based on his or her geographical interests and 2 ) various innovative interface designs for showing RSS-enabled information in an IPTV environment .

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


Web people search : results of the first evaluation and the plan for the second This paper presents the motivation , resources and results for the first Web People Search task , which was organized as part of the SemEval-2007 evaluation exercise . Also , we will describe a survey and proposal for a new task , `` attribute extraction '' , which is planned for inclusion in the second evaluation , planned for autumn , 2008 .

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

attributes of people
disambiguation
information extraction
person names


Web montage : a dynamic personalized start page Despite the connotation of the words `` browsing '' and `` surfing , '' web usage often follows routine patterns of access . However , few mechanisms exist to assist users with these routine tasks ; bookmarks or portal sites must be maintained manually and are insensitive to the user 's browsing context . To fill this void , we designed and implemented the montage system . A web montage is an ensemble of links and content fused into a single view . Such a coalesced view can be presented to the user whenever he or she opens the browser or returns to the start page . We pose a number of hypotheses about how users would interact with such a system , and test these hypotheses with a fielded user study . Our findings support some design decisions , such as using browsing context to tailor the montage , raise questions about others , and point the way toward future work .

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

adaptive user interfaces
adaptive web sites
personalization
user modeling


Combining RDF and XML schemas to enhance interoperability between metadata application profiles


The complex dynamics of collaborative tagging The debate within the Web community over the optimal means by which to organize information often pits formalized classifications against distributed collaborative tagging systems . A number of questions remain unanswered , however , regarding the nature of collaborative tagging systems including whether coherent categorization schemes can emerge from unsupervised tagging by users . This paper uses data from the social bookmarking site delicio . us to examine the dynamics of collaborative tagging systems . In particular , we examine whether the distribution of the frequency of use of tags for `` popular '' sites with a long history ( many tags and many users ) can be described by a power law distribution , often characteristic of what are considered complex systems . We produce a generative model of collaborative tagging in order to understand the basic dynamics behind tagging , including how a power law distribution of tags could arise . We empirically examine the tagging history of sites in order to determine how this distribution arises over time and to determine the patterns prior to a stable distribution . Lastly , by focusing on the high-frequency tags of a site where the distribution of tags is a stabilized power law , we show how tag co-occurrence networks for a sample domain of tags can be used to analyze the meaning of particular tags given their relationship to other tags .

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 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 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 B I 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 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


The semantic webscape : a view of the semantic web It has been a few years since the semantic Web was initiated by W3C , but its status has not been quantitatively measured . It is crucial to understand the status at this early stage , for researchers , developers and administrators to gain insight into what will come in this field . The objective of our work is to quantitatively measure and present the status of the semantic Web . We conduct a longitudinal study on the semantic Web pages to track trends in the use of semantic markup languages . This paper presents early results of this study with two historical data sets from October 2003 and October 2004 . Our results show that while it is very early stage of semantic Web adoption , its growth outpaces that of the entire Web for the period . Also , RDF ( Resource Description Framework ) has dominated among semantic markup languages , taking about 98 % of all semantic pages on the Web . It has been used in a variety of metadata annotation applications . This study shows that the most popular application is RSS ( RDF Site Summary ) for syndicating news and blogs , which takes more than 60 % of all semantic Web pages . It also shows that the use of OWL ( Web Ontology Language ) which was recommended by W3C in early 2004 has been increased 900 % for the period .

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

markup languages
ontology
rss
semantic web

content analysis and indexing
information search and retrieval


Measurement and analysis of cyberlocker services Cyberlocker Services ( CLS ) such as RapidShare and Megaupload have recently become popular . The decline of Peer-to-Peer ( P2P ) file sharing has prompted various services including CLS to replace it . We propose a comprehensive multi-level characterization of the CLS ecosystem . We answer three research questions : ( a ) what is a suitable measurement infrastructure for gathering CLS workloads ; ( b ) what are the characteristics of the CLS ecosystem ; and ( c ) what are the implications of CLS on Web 2.0 ( and the Internet ) . To the best of our knowledge , this work is the first to characterize the CLS ecosystem . The work will highlight the content , usage , performance , infrastructure , quality of service , and evolution characteristics of CLS .

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

cyberlockers
file hosting services
web 2.0


Latent space domain transfer between high dimensional overlapping distributions Transferring knowledge from one domain to another is challenging due to a number of reasons . Since both conditional and marginal distribution of the training data and test data are non-identical , model trained in one domain , when directly applied to a different domain , is usually low in accuracy . For many applications with large feature sets , such as text document , sequence data , medical data , image data of different resolutions , etc. two domains usually do not contain exactly the same features , thus introducing large numbers of `` missing values '' when considered over the union of features from both domains . In other words , its marginal distributions are at most overlapping . In the same time , these problems are usually high dimensional , such as , several thousands of features . Thus , the combination of high dimensionality and missing values make the relationship in conditional probabilities between two domains hard to measure and model . To address these challenges , we propose a framework that first brings the marginal distributions of two domains closer by `` filling up '' those missing values of disjoint features . Afterwards , it looks for those comparable sub-structures in the `` latent-space '' as mapped from the expanded feature vector , where both marginal and conditional distribution are similar . With these sub-structures in latent space , the proposed approach then find common concepts that are transferable across domains with high probability . During prediction , unlabeled instances are treated as `` queries '' , the mostly related labeled instances from out-domain are retrieved , and the classification is made by weighted voting using retrieved out-domain examples . We formally show that importing feature values across domains and latent semantic index can jointly make the distributions of two related domains easier to measure than in original feature space , the nearest neighbor method employed to retrieve related out domain examples is bounded in error when predicting in-domain examples . Software and datasets are available for download .

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

information search and retrieval
missing value
text mining
transfer learning


A uniform approach to accelerated PageRank computation In this note we consider a simple reformulation of the traditional power iteration algorithm for computing the stationary distribution of a Markov chain . Rather than communicate their current probability values to their neighbors at each step , nodes instead communicate only changes in probability value . This reformulation enables a large degree of flexibility in the manner in which nodes update their values , leading to an array of optimizations and features , including faster convergence , efficient incremental updating , and a robust distributed implementation . While the spirit of many of these optimizations appear in previous literature , we observe several cases where this unification simplifies previous work , removing technical complications and extending their range of applicability . We implement and measure the performance of several optimizations on a sizable ( 34M node ) web subgraph , seeing significant composite performance gains , especially for the case of incremental recomputation after changes to the web graph .

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

information search and retrieval
link analysis
random walks


Citizen sensor data mining , social media analytics and development centric web applications With the rapid rise in the popularity of social media ( 500M + Facebook users , 100M + twitter users ) , and near ubiquitous mobile access ( 4 + billion actively-used mobile phones ) , the sharing of observations and opinions has become common-place ( nearly 100M tweets a day , 1.8 trillion SMSs in US last year ) . This has given us an unprecedented access to the pulse of a populace and the ability to perform analytics on social data to support a variety of socially intelligent applications -- be it towards targeted online content delivery , crisis management , organizing revolutions or promoting social development in underdeveloped and developing countries . This tutorial will address challenges and techniques for building applications that support a broad variety of users and types of social media . This tutorial will focus on social intelligence applications for social development , and cover the following research efforts in sufficient depth : 1 ) understanding and analysis of informal text , esp . microblogs ( e.g. , issues of cultural entity extraction and role of semantic\/background knowledge enhanced techniques ) , and 2 ) building social media analytics platforms . Technical insights will be coupled with identification of computational techniques and real-world examples .

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

people-content-network view of social media


Learning to map between ontologies on the semantic web Ontologies play a prominent role on the Semantic Web . They make possible the widespread publication of machine understandable data , opening myriad opportunities for automated information processing . However , because of the Semantic Web 's distributed nature , data on it will inevitably come from many different ontologies . Information processing across ontologies is not possible without knowing the semantic mappings between their elements . Manually finding such mappings is tedious , error-prone , and clearly not possible at the Web scale . Hence , the development of tools to assist in the ontology mapping process is crucial to the success of the Semantic Web . We describe glue , a system that employs machine learning techniques to find such mappings . Given two ontologies , for each concept in one ontology glue finds the most similar concept in the other ontology . We give well-founded probabilistic definitions to several practical similarity measures , and show that glue can work with all of them . This is in contrast to most existing approaches , which deal with a single similarity measure . Another key feature of glue is that it uses multiple learning strategies , each of which exploits a different type of information either in the data instances or in the taxonomic structure of the ontologies . To further improve matching accuracy , we extend glue to incorporate commonsense knowledge and domain constraints into the matching process . For this purpose , we show that relaxation labeling , a well-known constraint optimization technique used in computer vision and other fields , can be adapted to work efficiently in our context . Our approach is thus distinguished in that it works with a variety of well-defined similarity notions and that it efficiently incorporates multiple types of knowledge . We describe a set of experiments on several real-world domains , and show that glue proposes highly accurate semantic mappings .

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

learning
ontology mapping
relaxation labeling
semantic web

heterogeneous databases
machine learning


Mining for personal name aliases on the web We propose a novel approach to find aliases of a given name from the web . We exploit a set of known names and their aliases as training data and extract lexical patterns that convey information related to aliases of names from text snippets returned by a web search engine . The patterns are then used to find candidate aliases of a given name . We use anchor texts and hyperlinks to design a word co-occurrence model and define numerous ranking scores to evaluate the association between a name and its candidate aliases . The proposed method outperforms numerous baselines and previous work on alias extraction on a dataset of personal names , achieving a statistically significant mean reciprocal rank of 0.6718 . Moreover , the aliases extracted using the proposed method improve recall by 20 % in a relation-detection task .

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

name alias extraction
semantic web
web mining


Exploiting web search engines to search structured databases Web search engines often federate many user queries to relevant structured databases . For example , a product related query might be federated to a product database containing their descriptions and specifications . The relevant structured data items are then returned to the user along with web search results . However , each structured database is searched in isolation . Hence , the search often produces empty or incomplete results as the database may not contain the required information to answer the query . In this paper , we propose a novel integrated search architecture . We establish and exploit the relationships between web search results and the items in structured databases to identify the relevant structured data items for a much wider range of queries . Our architecture leverages existing search engine components to implement this functionality at very low overhead . We demonstrate the quality and efficiency of our techniques through an extensive experimental study .

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

content analysis and indexing
entity extraction
entity ranking
entity search
information search and retrieval
structured database search


New objective functions for social collaborative filtering This paper examines the problem of social collaborative filtering ( CF ) to recommend items of interest to users in a social network setting . Unlike standard CF algorithms using relatively simple user and item features , recommendation in social networks poses the more complex problem of learning user preferences from a rich and complex set of user profile and interaction information . Many existing social CF methods have extended traditional CF matrix factorization , but have overlooked important aspects germane to the social setting . We propose a unified framework for social CF matrix factorization by introducing novel objective functions for training . Our new objective functions have three key features that address main drawbacks of existing approaches : ( a ) we fully exploit feature-based user similarity , ( b ) we permit direct learning of user-to-user information diffusion , and ( c ) we leverage co-preference ( dis ) agreement between two users to learn restricted areas of common interest . We evaluate these new social CF objectives , comparing them to each other and to a variety of ( social ) CF baselines , and analyze user behavior on live user trials in a custom-developed Facebook App involving data collected over five months from over 100 App users and their 37,000 + friends .

O O O O 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 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


Randomization tests for distinguishing social influence and homophily effects Relational autocorrelation is ubiquitous in relational domains . This observed correlation between class labels of linked instances in a network ( e.g. , two friends are more likely to share political beliefs than two randomly selected people ) can be due to the effects of two different social processes . If social influence effects are present , instances are likely to change their attributes to conform to their neighbor values . If homophily effects are present , instances are likely to link to other individuals with similar attribute values . Both these effects will result in autocorrelated attribute values . When analyzing static relational networks it is impossible to determine how much of the observed correlation is due each of these factors . However , the recent surge of interest in social networks has increased the availability of dynamic network data . In this paper , we present a randomization technique for temporal network data where the attributes and links change over time . Given data from two time steps , we measure the gain in correlation and assess whether a significant portion of this gain is due to influence and\/or homophily . We demonstrate the efficacy of our method on semi-synthetic data and then apply the method to a real-world social networks dataset , showing the impact of both influence and homophily effects .

B 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 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 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 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 O O O O O O B O O

homophily
randomization
social influence
social networks


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Ranking definitions with supervised learning methods This paper is concerned with the problem of definition search . Specifically , given a term , we are to retrieve definitional excerpts of the term and rank the extracted excerpts according to their likelihood of being good definitions . This is in contrast to the traditional approaches of either generating a single combined definition or simply outputting all retrieved definitions . Definition ranking is essential for the task . Methods for performing definition ranking are proposed in this paper , which formalize the problem as either classification or ordinal regression . A specification for judging the goodness of a definition is given . We employ SVM as the classification model and Ranking SVM as the ordinal regression model respectively , such that they rank definition candidates according to their likelihood of being good definitions . Features for constructing the SVM and Ranking SVM models are defined . An enterprise search system based on this method has been developed and has been put into practical use . Experimental results indicate that the use of SVM and Ranking SVM can significantly outperform the baseline methods of using heuristic rules or employing the conventional information retrieval method of Okapi . This is true both when the answers are paragraphs and when they are sentences . Experimental results also show that SVM or Ranking SVM models trained in one domain can be adapted to another domain , indicating that generic models for definition ranking can be constructed .

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 I 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 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

miscellaneous
search of definitions
text mining
web mining
web search


Money , glory and cheap talk : analyzing strategic behavior of contestants in simultaneous crowdsourcing contests on TopCoder.com Crowdsourcing is a new Web phenomenon , in which a firm takes a function once performed in-house and outsources it to a crowd , usually in the form of an open contest . Designing efficient crowdsourcing mechanisms is not possible without deep understanding of incentives and strategic choices of all participants . This paper presents an empirical analysis of determinants of individual performance in multiple simultaneous crowdsourcing contests using a unique dataset for the world 's largest competitive software development portal : TopCoder.com . Special attention is given to studying the effects of the reputation system currently used by TopCoder.com on behavior of contestants . We find that individual specific traits together with the project payment and the number of project requirements are significant predictors of the final project quality . Furthermore , we find significant evidence of strategic behavior of contestants . High rated contestants face tougher competition from their opponents in the competition phase of the contest . In order to soften the competition , they move first in the registration phase of the contest , signing up early for particular projects . Although registration in TopCoder contests is non-binding , it deters entry of opponents in the same contest ; our lower bound estimate shows that this strategy generates significant surplus gain to high rated contestants . We conjecture that the reputation + cheap talk mechanism employed by TopCoder has a positive effect on allocative efficiency of simultaneous all-pay contests and should be considered for adoption in other crowdsourcing platforms .

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

cheap talk
contest
crowdsourcing
reputation

all-pay auction
electronic markets
entry deterrence
miscellaneous


Web page classification with heterogeneous data fusion Web pages are more than text and they contain much contextual and structural information , e.g. , the title , the meta data , the anchor text , etc. , each of which can be seen as a data source or are presentation . Due to the different dimensionality and different representing forms of these heterogeneous data sources , simply putting them together would not greatly enhance the classification performance . We observe that via a kernel function , different dimensions and types of data sources can be represented into acommon format of kernel matrix , which can be seen as a generalized similarity measure between a pair of web pages . In this sense , a kernel learning approach is employed to fuse these heterogeneous data sources . The experimental results on a collection of the ODP database validate the advantages of the proposed method over traditional methods based on any single data source and the uniformly weighted combination of them .

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


XVM : a bridge between xml data and its behavior XML has become one of the core technologies for contemporary business applications , especially web-based applications . To facilitate processing of diverse XML data , we propose an extensible , integrated XML processing architecture , the XML Virtual Machine ( XVM ) , which connects XML data with their behaviors . At the same time , the XVM is also a framework for developing and deploying XML-based applications . Using component-based techniques , the XVM supports arbitrary granularity and provides a high degree of modularity and reusability . XVM components are dynamically loaded and composed during XML data processing . Using the XVM , both client-side and server-side XML applications can be developed and deployed in an integrated way . We also present an XML application container built on top of the XVM along with several sample applications to demonstrate the applicability of the XVM framework .

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

web applications
xml applications
xml processing


Identifying enrichment candidates in textbooks Many textbooks written in emerging countries lack clear and adequate coverage of important concepts . We propose a technological solution for algorithmically identifying those sections of a book that are not well written and could benefit from better exposition . We provide a decision model based on the syntactic complexity of writing and the dispersion of key concepts . The model parameters are learned using a tune set which is algorithmically generated using a versioned authoritative web resource as a proxy . We evaluate the proposed methodology over a corpus of Indian textbooks which demonstrates its effectiveness in identifying enrichment candidates .

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

education
information search and retrieval
readability


Copyright protection on the web : a hybrid digital video watermarking scheme Video is one of the most popular data shared in the Web , and the protection of video copyright is of vast interest . In this paper , we present a comprehensive approach for protecting and managing video copyrights in the Internet with watermarking techniques . We propose a novel hybrid digital video watermarking scheme with scrambled watermarks and error correction codes . The effectiveness of this scheme is verified through a series of experiments , and the robustness of our approach is demonstrated using the criteria of the latest StirMark test .

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

digital watermarking
scene change
security and protection


A geographical analysis of knowledge production in computer science We analyze knowledge production in Computer Science by means of coauthorship networks . For this , we consider 30 graduate programs of different regions of the world , being 8 programs in Brazil , 16 in North America ( 3 in Canada and 13 in the United States ) , and 6 in Europe ( 2 in France , 1 in Switzerland and 3 in the United Kingdom ) . We use a dataset that consists of 176,537 authors and 352,766 publication entries distributed among 2,176 publication venues . The results obtained for different metrics of collaboration social networks indicate the process of knowledge creation has changed differently for each region . Research is increasingly done in teams across different fields of Computer Science . The size of the giant component indicates the existence of isolated collaboration groups in the European network , contrasting to the degree of connectivity found in the Brazilian and North-American counterparts . We also analyzed the temporal evolution of the social networks representing the three regions . The number of authors per paper experienced an increase in a time span of 12 years . We observe that the number of collaborations between authors grows faster than the number of authors , benefiting from the existing network structure . The temporal evolution shows differences between well-established fields , such as Databases and Computer Architecture , and emerging fields , like Bioinformatics and Geoinformatics . The patterns of collaboration analyzed in this paper contribute to an overall understanding of Computer Science research in different geographical regions that could not be achieved without the use of complex networks and a large publication database .

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

coauthorship networks
collaboration social networks
computer science


Learning how to learn with web contents Learning Web contents requires learners not only to navigate the Web pages to construct their own knowledge from the contents learned at and between the pages , but also to control their own navigation and knowledge construction processes . However , it is not so easy to control the learning processes . The main issue addressed is how to help learners learn how to learn with Web contents . This paper discusses how to design a meta-learning tool .

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

hyperspace
learning affordance
meta-learning
navigational learning


Constructing travel itineraries from tagged geo-temporal breadcrumbs Vacation planning is a frequent laborious task which requires skilled interaction with a multitude of resources . This paper develops an end-to-end approach for constructing intra-city travel itineraries automatically by tapping a latent source reflecting geo-temporal breadcrumbs left by millions of tourists . In particular , the popular rich media sharing site , Flickr , allows photos to be stamped by the date and time of when they were taken , and be mapped to Points Of Interest ( POIs ) by latitude-longitude information as well as semantic metadata ( e.g. , tags ) that describe them . Our extensive user study on a `` crowd-sourcing '' marketplace ( Amazon Mechanical Turk ) , indicates that high quality itineraries can be automatically constructed from Flickr data , when compared against popular professionally generated bus tours .

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

geo-tags
media applications
orienteering problem
travel itinerary


Facetnet : a framework for analyzing communities and their evolutions in dynamic networks We discover communities from social network data , and analyze the community evolution . These communities are inherent characteristics of human interaction in online social networks , as well as paper citation networks . Also , communities may evolve over time , due to changes to individuals ' roles and social status in the network as well as changes to individuals ' research interests . We present an innovative algorithm that deviates from the traditional two-step approach to analyze community evolutions . In the traditional approach , communities are first detected for each time slice , and then compared to determine correspondences . We argue that this approach is inappropriate in applications with noisy data . In this paper , we propose FacetNet for analyzing communities and their evolutions through a robust unified process . In this novel framework , communities not only generate evolutions , they also are regularized by the temporal smoothness of evolutions . As a result , this framework will discover communities that jointly maximize the fit to the observed data and the temporal evolution . Our approach relies on formulating the problem in terms of non-negative matrix factorization , where communities and their evolutions are factorized in a unified way . Then we develop an iterative algorithm , with proven low time complexity , which is guaranteed to converge to an optimal solution . We perform extensive experimental studies , on both synthetic datasets and real datasets , to demonstrate that our method discovers meaningful communities and provides additional insights not directly obtainable from traditional 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 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 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 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

community net
evolution net
non-negative matrix factorization
soft membership


An enhanced model for searching in semantic portals Semantic Portal is the next generation of web portals that are powered by Semantic Web technologies for improved information sharing and exchange for a community of users . Current methods of searching in Semantic Portals are limited to keyword-based search using information retrieval ( IR ) techniques , ontology-based formal query and reasoning , or a simple combination of the two . In this paper , we propose an enhanced model that tightly integrates IR with formal query and reasoning to fully utilize both textual and semantic information for searching in Semantic Portals . The model extends the search capabilities of existing methods and can answer more complex search requests . The ideas in a fuzzy description logic ( DL ) IR model and a formal DL query method are employed and combined in our model . Based on the model , a semantic search service is implemented and evaluated . The evaluation shows very large improvements over existing methods .

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

fuzzy description logic
information retrieval
semantic portal
semantic search

fuzzy reasoning
information search and retrieval


Graffiti : node labeling in heterogeneous networks We introduce a multi-label classification model and algorithm for labeling heterogeneous networks , where nodes belong to different types and different types have different sets of classification labels . We present a graph-based approach which models the mutual influence between nodes in the network as a random walk . When viewing class labels as `` colors '' , the random surfer is `` spraying '' different node types with different color palettes ; hence the name Graffiti . We demonstrate the performance gains of our method by comparing it to three state-of-the-art techniques for graph-based classification .

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


Document hierarchies from text and links Hierarchical taxonomies provide a multi-level view of large document collections , allowing users to rapidly drill down to fine-grained distinctions in topics of interest . We show that automatically induced taxonomies can be made more robust by combining text with relational links . The underlying mechanism is a Bayesian generative model in which a latent hierarchical structure explains the observed data -- thus , finding hierarchical groups of documents with similar word distributions and dense network connections . As a nonparametric Bayesian model , our approach does not require pre-specification of the branching factor at each non-terminal , but finds the appropriate level of detail directly from the data . Unlike many prior latent space models of network structure , the complexity of our approach does not grow quadratically in the number of documents , enabling application to networks with more than ten thousand nodes . Experimental results on hypertext and citation network corpora demonstrate the advantages of our hierarchical , multimodal approach .

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

bayesian generative models
hierarchical clustering
learning
stochastic block models
topic models


Performance of compressed inverted list caching in search engines Due to the rapid growth in the size of the web , web search engines are facing enormous performance challenges . The larger engines in particular have to be able to process tens of thousands of queries per second on tens of billions of documents , making query throughput a critical issue . To satisfy this heavy workload , search engines use a variety of performance optimizations including index compression , caching , and early termination . We focus on two techniques , inverted index compression and index caching , which play a crucial rule in web search engines as well as other high-performance information retrieval systems . We perform a comparison and evaluation of several inverted list compression algorithms , including new variants of existing algorithms that have not been studied before . We then evaluate different inverted list caching policies on large query traces , and finally study the possible performance benefits of combining compression and caching . The overall goal of this paper is to provide an updated discussion and evaluation of these two techniques , and to show how to select the best set of approaches and settings depending on parameter such as disk speed and main memory cache size .

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

index caching
index compression
search engines


Towards robust service compositions in the context of functionally diverse services Web service composition provides a means of customized and flexible integration of service functionalities . Quality-of-Service ( QoS ) optimization algorithms select services in order to adapt workflows to the non-functional requirements of the user . With increasing number of services in a workflow , previous approaches fail to achieve a sufficient reliability . Moreover , expensive ad-hoc replanning is required to deal with service failures . The major problem with such sequential application of planning and replanning is that it ignores the potential costs during the initial planning and they consequently are hidden from the decision maker . Our basic idea to overcome this substantial problem is to compute a QoS optimized selection of service clusters that includes a sufficient number of backup services for each service employed . To support the human decision maker in the service selection task , our approach considers the possible repair costs directly in the initial composition . On the basis of a multi-objective approach and using a suitable service selection interface , the decision maker can select compositions in line with his\/her personal risk preferences .

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

multi-objective optimization
on-line information services
qos-aware service composition
robustness
service computing


AwareDAV : a generic WebDAV notification framework and implementation WebDAV needs awareness support in order to be a full-fledged collaboration system , This paper introduces AwareDAV , a new WebDAV extension framework enabling shared awareness through event notification . By extending the WebDAV protocol with seven new request-methods and an extensible XML based event subscription scheme , AwareDAV supports fine grained event subscriptions over a range of transport mechanisms and enables a wide range of collaboration scenarios . This paper describes the design of AwareDAV , its API , experiences with its initial implementation , as well as a comparison with Microsoft Exchange and WebDAV-notify .

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


Testbed for information extraction from deep web Search results generated by searchable databases are served dynamically and far larger than the static documents on the Web . These results pages have been referred to as the Deep Web . We need to extract the target data in results pages to integrate them on different searchable databases . We propose a test bed for information extraction from search results . We chose 100 databases randomly from 114,540 pages with search forms . Therefore , these databases have a good variety . We selected 51 databases which include URLs in a results pageand manually identify target information to be extracted . We also suggest evaluation measures for comparing extraction methods and methods for extending the target data .

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 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

meta search
performance evaluation
wrapper


Capturing the essentials of federated systems Today , the Web is increasingly used as a platform for distributed services , which transcend organizational boundaries to form federated applications . Consequently , there is a growing interest in the architectural aspect of Web-based systems , i.e. the composition of the overall solution into individual Web applications and Web services from different parties . The design and evolution of federated systems calls for models that give an overview of the structural as well as trust-specific composition and reflect the technical details of the various accesses . We introduce the WebComposition Architecture Model ( WAM ) as an overall modeling approach tailored to aspects of highly distributed systems with federation as an integral factor .

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

architecture
federation
modeling
web services


SecuBat : a web vulnerability scanner As the popularity of the web increases and web applications become tools of everyday use , the role of web security has been gaining importance as well . The last years have shown a significant increase in the number of web-based attacks . For example , there has been extensive press coverage of recent security incidences involving the loss of sensitive credit card information belonging to millions of customers . Many web application security vulnerabilities result from generic input validation problems . Examples of such vulnerabilities are SQL injection and Cross-Site Scripting ( XSS ) . Although the majority of web vulnerabilities are easy to understand and to avoid , many web developers are , unfortunately , not security-aware . As a result , there exist many web sites on the Internet that are vulnerable . This paper demonstrates how easy it is for attackers to automatically discover and exploit application-level vulnerabilities in a large number of web applications . To this end , we developed SecuBat , a generic and modular web vulnerability scanner that , similar to a port scanner , automatically analyzes web sites with the aim of finding exploitable SQL injection and XSS vulnerabilities . Using SecuBat , we were able to find many potentially vulnerable web sites . To verify the accuracy of SecuBat , we picked one hundred interesting web sites from the potential victim list for further analysis and confirmed exploitable flaws in the identified web pages . Among our victims were well-known global companies and a finance ministry . Of course , we notified the administrators of vulnerable sites about potential security problems . More than fifty responded to request additional information or to report that the security hole was closed .

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

automated vulnerability detection
crawling
cross-site scripting
miscellaneous
security and protection


Mining web logs to improve website organization


Efficient search in large textual collections with redundancy Current web search engines focus on searching only themost recentsnapshot of the web . In some cases , however , it would be desirableto search over collections that include many different crawls andversions of each page . One important example of such a collectionis the Internet Archive , though there are many others . Sincethe data size of such an archive is multiple times that of a singlesnapshot , this presents us with significant performance challenges . Current engines use various techniques for index compression andoptimized query execution , but these techniques do not exploit thesignificant similarities between different versions of a page , or betweendifferent pages . In this paper , we propose a general framework for indexing andquery processing of archival collections and , more generally , anycollections with a sufficient amount of redundancy . Our approachresults in significant reductions in index size and query processingcosts on such collections , and it is orthogonal to and can be combinedwith the existing techniques . It also supports highly efficientupdates , both locally and over a network . Within this framework , we describe and evaluate different implementations that trade offindex size versus CPU cost and other factors , and discuss applicationsranging from archival web search to local search of web sites , email archives , or file systems . We present experimental resultsbased on search engine query log and a large collection consistingof multiple crawls .

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 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

index compression
query execution
search engines

content analysis and indexing
inverted index
redundancy elimination


Alhambra : a system for creating , enforcing , and testing browser security policies Alhambra is a browser-based system designed to enforce and test web browser security policies . At the core of Alhambra is a policy-enhanced browser supporting fine-grain security policies that restrict web page contents and execution . Alhambra requires no server-side modifications or additions to the web application . Policies can restrict the construction of the document as well as the execution of JavaScript using access control rules and a taint-tracking engine . Using the Alhambra browser , we present two security policies that we have built using our architecture , both designed to prevent cross-site scripting . The first policy uses a taint-tracking engine to prevent cross-site scripting attacks that exploit bugs in the client-side of the web applications . The second one uses browsing history to create policies that restrict the contents of documents and prevent the inclusion of malicious content . Using Alhambra we analyze the impact of policies on the compatibility of web pages . To test compatibility , Alhambra supports revisiting user-generated browsing sessions and comparing multiple security policies in parallel to quickly and automatically evaluate security policies . To compare security policies for identical pages we have also developed useful comparison metrics that quantify differences between identical pages executed with different security policies . Not only do we show that our policies are effective with minimal compatibility cost , we also demonstrate that Alhambra can enforce strong security policies and provide quantitative evaluation of the differences introduced by security policies .

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

cross-site scripting
security and protection
web security


On the analysis of cascading style sheets Developing and maintaining cascading style sheets ( CSS ) is an important issue to web developers as they suffer from the lack of rigorous methods . Most existing means rely on validators that check syntactic rules , and on runtime debuggers that check the behavior of a CSS style sheet on a particular document instance . However , the aim of most style sheets is to be applied to an entire set of documents , usually defined by some schema . To this end , a CSS style sheet is usually written w.r.t. a given schema . While usual debugging tools help reducing the number of bugs , they do not ultimately allow to prove properties over the whole set of documents to which the style sheet is intended to be applied . We propose a novel approach to fill this lack . We introduce ideas borrowed from the fields of logic and compile-time verification for the analysis of CSS style sheets . We present an original tool based on recent advances in tree logics . The tool is capable of statically detecting a wide range of errors ( such as empty CSS selectors and semantically equivalent selectors ) , as well as proving properties related to sets of documents ( such as coverage of styling information ) , in the presence or absence of schema information . This new tool can be used in addition to existing runtime debuggers to ensure a higher level of quality of CSS style sheets .

O O O O O B I 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 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 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 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 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 B B I O