Rewriting queries on SPARQL views The problem of answering SPARQL queries over virtual SPARQL views is commonly encountered in a number of settings , including while enforcing security policies to access RDF data , or when integrating RDF data from disparate sources . We approach this problem by rewriting SPARQL queries over the views to equivalent queries over the underlying RDF data , thus avoiding the costs entailed by view materialization and maintenance . We show that SPARQL query rewriting combines the most challenging aspects of rewriting for the relational and XML cases : like the relational case , SPARQL query rewriting requires synthesizing multiple views ; like the XML case , the size of the rewritten query is exponential to the size of the query and the views . In this paper , we present the first native query rewriting algorithm for SPARQL . For an input SPARQL query over a set of virtual SPARQL views , the rewritten query resembles a union of conjunctive queries and can be of exponential size . We propose optimizations over the basic rewriting algorithm to ( i ) minimize each conjunctive query in the union ; ( ii ) eliminate conjunctive queries with empty results from evaluation ; and ( iii ) efficiently prune out big portions of the search space of empty rewritings . The experiments , performed on two RDF stores , show that our algorithms are scalable and independent of the underlying RDF stores . Furthermore , our optimizations have order of magnitude improvements over the basic rewriting algorithm in both the rewriting size and evaluation time .

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


Updating pagerank with iterative aggregation We present an algorithm for updating the PageRank vector ( 1 ) . Due to the scale of the web , Google only updates its famous PageRank vector on a monthly basis . However , the Web changes much more frequently . Drastically speeding the PageRank computation can lead to fresher , more accurate rankings of the webpages retrieved by search engines . It can also make the goal of real-time personalized rankings within reach . On two small subsets of the web , our algorithm updates PageRank using just 25 % and 14 % , respectively , of the time required by the original PageRank algorithm . Our algorithm uses iterative aggregation techniques ( 7 , 8 ) to focus on the slow-converging states of the Markov chain . The most exciting feature of this algorithm is that it can be joined with other PageRank acceleration methods , such as the dangling node lumpability algorithm ( 6 ) , quadratic extrapolation ( 4 ) , and adaptive PageRank ( 3 ) , to realize even greater speedups ( potentially a factor of 60 or more speedup when all algorithms are combined ) . every few weeks . Our solution harnesses the power of iterative aggregation principles for Markov chains to allow for much more frequent updates to the valuable ranking vectors .

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

aggregation
markov chains
pagerank
updating

disaggregation
general
link analysis
power method
stationary vector


Are web users really Markovian ? User modeling on the Web has rested on the fundamental assumption of Markovian behavior -- a user 's next action depends only on her current state , and not the history leading up to the current state . This forms the underpinning of PageRank web ranking , as well as a number of techniques for targeting advertising to users . In this work we examine the validity of this assumption , using data from a number of Web settings . Our main result invokes statistical order estimation tests for Markov chains to establish that Web users are not , in fact , Markovian . We study the extent to which the Markovian assumption is invalid , and derive a number of avenues for further research .

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


Opinion integration through semi-supervised topic modeling Web 2.0 technology has enabled more and more people to freely express their opinions on the Web , making the Web an extremely valuable source for mining user opinions about all kinds of topics . In this paper we study how to automatically integrate opinions expressed in a well-written expert review with lots of opinions scattering in various sources such as blogspaces and forums . We formally define this new integration problem and propose to use semi-supervised topic models to solve the problem in a principled way . Experiments on integrating opinions about two quite different topics ( a product and a political figure ) show that the proposed method is effective for both topics and can generate useful aligned integrated opinion summaries . The proposed method is quite general . It can be used to integrate a well written review with opinions in an arbitrary text collection about any topic to potentially support many interesting applications in multiple domains .

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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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
probabilistic topic modeling
semi-supervised


The role of social networks in information diffusion Online social networking technologies enable individuals to simultaneously share information with any number of peers . Quantifying the causal effect of these mediums on the dissemination of information requires not only identification of who influences whom , but also of whether individuals would still propagate information in the absence of social signals about that information . We examine the role of social networks in online information diffusion with a large-scale field experiment that randomizes exposure to signals about friends ' information sharing among 253 million subjects in situ . Those who are exposed are significantly more likely to spread information , and do so sooner than those who are not exposed . We further examine the relative role of strong and weak ties in information propagation . We show that , although stronger ties are individually more influential , it is the more abundant weak ties who are responsible for the propagation of novel information . This suggests that weak ties may play a more dominant role in the dissemination of information online than currently believed .

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


Ranking community answers via analogical reasoning Due to the lexical gap between questions and answers , automatically detecting right answers becomes very challenging for community question-answering sites . In this paper , we propose an analogical reasoning-based method . It treats questions and answers as relational data and ranks an answer by measuring the analogy of its link to a query with the links embedded in previous relevant knowledge ; the answer that links in the most analogous way to the new question is assumed to be the best answer . We based our experiments on 29.8 million Yahoo ! Answer question-answer threads and showed the effectiveness of the approach .

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


Information retrieval in P2P networks using genetic algorithm Hybrid Peer-to-Peer ( P2P ) networks based on the direct connection model have two shortcomings which are high bandwidth consumption and poor semi-parallel search . However , they can further be improved by the query propagation model . In this paper , we propose a novel query routing strategy called GAroute based on the query propagation model . By giving the current P2P network topology and relevance level of each peer , GAroute returns a list of query routing paths that cover as many relevant peers as possible . We model this as the Longest Path Problem in a directed graph which is NP-complete and we obtain high quality ( 0.95 in 100 peers ) approximate solutions in polynomial time by using Genetic Algorithm ( GA ) . We describe the problem modeling and proposed GA for finding long paths . Finally , we summarize the experimental results which measure the scalability and quality of different searching algorithms . According to these results , GAroute works well in some large scaled P2P networks .

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

genetic algorithm
longest path problem
p2p
query routing


Dynamics of bid optimization in online advertisement auctions We consider the problem of online keyword advertising auctions among multiple bidders with limited budgets , and study a natural bidding heuristic in which advertisers attempt to optimize their utility by equalizing their return-on-investment across all keywords . We show that existing auction mechanisms combined with this heuristic can experience cycling ( as has been observed in many current systems ) , and therefore propose a modified class of mechanisms with small random perturbations . This perturbation is reminiscent of the small time-dependent perturbations employed in the dynamical systems literature to convert many types of chaos into attracting motions . We show that the perturbed mechanism provably converges in the case of first-price auctions and experimentally converges in the case of second-price auctions . Moreover , the point of convergence has a natural economic interpretation as the unique market equilibrium in the case of first-price mechanisms . In the case of second-price auctions , we conjecture that it converges to the `` supply-aware '' market equilibrium . Thus , our results can be alternatively described as a tâtonnement process for convergence to market equilibriumin which prices are adjusted on the side of the buyers rather than the sellers . We also observe that perturbation in mechanism design is useful in a broader context : In general , it can allow bidders to `` share '' a particular item , leading to stable allocations and pricing for the bidders , and improved revenue for the auctioneer .

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

analysis of algorithms and problem complexity


Effort estimation : how valuable is it for a web company to use a cross-company data set , compared to using its own single-company data set ? Previous studies comparing the prediction accuracy of effort models built using Web cross - and single-company data sets have been inconclusive , and as such replicated studies are necessary to determine under what circumstances a company can place reliance on a cross-company effort model . This paper therefore replicates a previous study by investigating how successful a cross-company effort model is : i ) to estimate effort for Web projects that belong to a single company and were not used to build the cross-company model ; ii ) compared to a single-company effort model . Our single-company data set had data on 15 Web projects from a single company and our cross-company data set had data on 68 Web projects from 25 different companies . The effort estimates used in our analysis were obtained by means of two effort estimation techniques , namely forward stepwise regression and case-based reasoning . Our results were similar to those from the replicated study , showing that predictions based on the single-company model were significantly more accurate than those based on the cross-company model .

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 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 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 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

effort estimation
stepwise regression
web projects

case-based reasoning
cross-company effort model
single-company effort model
web applications


Supervised rank aggregation This paper is concerned with rank aggregation , the task of combining the ranking results of individual rankers at meta-search . Previously , rank aggregation was performed mainly by means of unsupervised learning . To further enhance ranking accuracies , we propose employing supervised learning to perform the task , using labeled data . We refer to the approach as Supervised Rank Aggregation . We set up a general framework for conducting Supervised Rank Aggregation , in which learning is formalized an optimization which minimizes disagreements between ranking results and the labeled data . As case study , we focus on Markov Chain based rank aggregation in this paper . The optimization for Markov Chain based methods is not a convex optimization problem , however , and thus is hard to solve . We prove that we can transform the optimization problem into that of Semidefinite Programming and solve it efficiently . Experimental results on meta-searches show that Supervised Rank Aggregation can significantly outperform existing unsupervised methods .

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

markov chain
rank aggregation
supervised learning

performance evaluation
semidefinite progromming


Aliasing on the world wide web : prevalence and performance implications Aliasing occurs in Web transactions when requests containing different URLs elicit replies containing identical data payloads . Conventional caches associate stored data with URLs and can therefore suffer redundant payload transfers due to aliasing and other causes . Existing research literature , however , says little about the prevalence of aliasing in user-initiated transactions , or about redundant payload transfers in conventional Web cache hierarchies . This paper quantifies the extent of aliasing and the performance impact of URL-indexed cache management using a large client trace from WebTV Networks . Fewer than 5 % of reply payloads are aliased ( referenced via multiple URLs ) but over 54 % of successful transactions involve aliased payloads . Aliased payloads account for under 3.1 % of the trace 's `` working set size '' ( sum of payload sizes ) but over 36 % of bytes transferred . For the WebTV workload , roughly 10 % of payload transfers to browser caches and 23 % of payload transfers to a shared proxy are redundant , assuming infinite-capacity conventional caches . Our analysis of a large proxy trace from Compaq Corporation yields similar results.URL-indexed caching does not entirely explain the large number of redundant proxy-to-browser payload transfers previously reported in the WebTV system . We consider other possible causes of redundant transfers ( e.g. , reply metadata and browser cache management policies ) and discuss a simple hop-by-hop protocol extension that completely eliminates all redundant transfers , regardless of cause .

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

aliasing
cache hierarchies
caching
redundant transfers
world wide web

applications
dtd
duplicate suppression
duplicate transfer detection
http
hypertext transfer protocol
performance analysis
resource modification
www
zipf's law


Improving recommendation lists through topic diversification In this work we present topic diversification , a novel method designed to balance and diversify personalized recommendation lists in order to reflect the user 's complete spectrum of interests . Though being detrimental to average accuracy , we show that our method improves user satisfaction with recommendation lists , in particular for lists generated using the common item-based collaborative filtering algorithm . Our work builds upon prior research on recommender systems , looking at properties of recommendation lists as entities in their own right rather than specifically focusing on the accuracy of individual recommendations . We introduce the intra-list similarity metric to assess the topical diversity of recommendation lists and the topic diversification approach for decreasing the intra-list similarity . We evaluate our method using book recommendation data , including offline analysis on 361 , ! , 349 ratings and an online study involving more than 2 , ! , 100 subjects .

O O O O O B 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 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 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

accuracy
collaborative filtering
diversification
recommender systems


Adaptive push-pull : disseminating dynamic web data

data dissemination
dynamic data
pull
push
resiliency
scalability
temporal coherency
world wide web


We know who you followed last summer : inferring social link creation times in twitter Understanding a network 's temporal evolution appears to require multiple observations of the graph over time . These often expensive repeated crawls are only able to answer questions about what happened from observation to observation , and not what happened before or between network snapshots . Contrary to this picture , we propose a method for Twitter 's social network that takes a single static snapshot of network edges and user account creation times to accurately infer when these edges were formed . This method can be exact in theory , and we demonstrate empirically for a large subset of Twitter relationships that it is accurate to within a few hours in practice . We study users who have a very large number of edges or who are recommended by Twitter . We examine the graph formed by these nearly 1,800 Twitter celebrities and their 862 million edges in detail , showing that a single static snapshot can give novel insights about Twitter 's evolution . We conclude from this analysis that real-world events and changes to Twitter 's interface for recommending users strongly influence network growth .

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

graph analysis
large-scale data collection
miscellaneous
network evolution
online social networks
user behavior


Social and semantics analysis via non-negative matrix factorization Social media such as Web forum often have dense interactions between user and content where network models are often appropriate for analysis . Joint non-negative matrix factorization model of participation and content data can be viewed as a bipartite graph model between users and media and is proposed for analysis social media . The factorizations allow simultaneous automatic discovery of leaders and sub-communities in the Web forum as well as the core latent topics in the forum . Results on topic detection of Web forums and cluster analysis show that social features are highly effective for forum analysis .

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

algorithm
graph theory
hypertext/hypermedia
learning


P-tree : a p2p index for resource discovery applications We propose a new distributed , fault-tolerant Peer-to-Peer index structure for resource discovery applications called the P-tree . P-trees efficiently support range queries in addition to equality queries .

O O O O O O B I 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


Representing personal web information using a topic-oriented interface Nowadays , Web activities have become daily practice for people . It is therefore essential to organize and present this continuously increasing Web information in a more usable manner . In this paper , we developed a novel approach to reorganize personal Web information as a topic-oriented interface . In our approach , we proposed to utilize anchor , title and URL information to represent content information for the browsed Web pages rather than the content body . Furthermore , we explored three methods to organize personal Web information : 1 ) top-down statistical clustering ; 2 ) salience phrase based clustering ; and 3 ) support vector machine ( SVM ) based classification . Finally , we conducted a usability study to verify the effectiveness of our proposed solution . The experimental results demonstrated that users could visit the pages that have been browsed previously more easily with our approach than existing solutions .

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

topic classfication
user information mining
user interface


Detecting nepotistic links by language model disagreement In this short note we demonstrate the applicability of hyperlink downweighting by means of language model disagreement . The method filters out hyperlinks with no relevance to the target page without the need of white and blacklists or human interaction . We fight various forms of nepotism such as common maintainers , ads , link exchanges or misused affiliate programs . Our method is tested on a 31 M page crawl of the . de domain with a manually classified 1000-page random sample .

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

anchor text
information search and retrieval
language modeling
link spam


Multi-objective ranking of comments on web With the explosion of information on any topic , the need for ranking is becoming very critical . Ranking typically depends on several aspects . Products , for example , have several aspects like price , recency , rating , etc. . Product ranking has to bring the `` best '' product which is recent and highly rated . Hence ranking has to satisfy multiple objectives . In this paper , we explore multi-objective ranking of comments using Hodge decomposition . While Hodge decomposition produces a globally consistent ranking , a globally inconsistent component is also present . We propose an active learning strategy for the reduction of this component . Finally , we develop techniques for online Hodge decomposition . We experimentally validate the ideas presented in this paper .

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


Towards liquid service oriented architectures The advent of Cloud computing platforms , and the growing pervasiveness of Multicore processor architectures have revealed the inadequateness of traditional programming models based on sequential computations , opening up many challenges for research on parallel programming models for building distributed , service-oriented systems . More in detail , the dynamic nature of Cloud computing and its virtualized infrastructure pose new challenges in term of application design , deployment and dynamic reconfiguration . An application developed to be delivered as a service in the Cloud has to deal with poorly understood issues such as elasticity , infinite scalability and portability across heterogeneous virtualized environments . In this position paper we define the problem of providing a novel parallel programming model for building application services that can be transparently deployed on multicore and cloud execution environments . To this end , we introduce and motivate a research plan for the definition of a novel programming framework for Web service-based applications . Our vision called `` Liquid Architecture '' is based on a programming model inspired by core ideas tied to the REST architectural style coupled with a self-configuring runtime that allows transparent deployment of Web services on a broad range of heterogeneous platforms , from multicores to clouds .

O O 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 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 B 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


Sampling search-engine results We consider the problem of efficiently sampling Web search engine query results . In turn , using a small random sample instead of the full set of results leads to efficient approximate algorithms for several applications , such as : Determining the set of categories in a given taxonomy spanned by the search results ; Finding the range of metadata values associated to the result set in order to enable `` multi-faceted search ; '' Estimating the size of the result set ; Data mining associations to the query terms . We present and analyze an efficient algorithm for obtaining uniform random samples applicable to any search engine based on posting lists and document-at-a-time evaluation . ( To our knowledge , all popular Web search engines , e.g. Google , Inktomi , AltaVista , AllTheWeb , belong to this class . ) Furthermore , our algorithm can be modified to follow the modern object-oriented approach whereby posting lists are viewed as streams equipped with a next method , and the next method for Boolean and other complex queries is built from the next method for primitive terms . In our case we show how to construct a basic next ( p ) method that samples term posting lists with probability p , and show how to construct next ( p ) methods for Boolean operators ( AND , OR , WAND ) from primitive methods . Finally , we test the efficiency and quality of our approach on both synthetic and real-world data .

B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 B 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
weighted and


Detecting semantic cloaking on the web By supplying different versions of a web page to search engines and to browsers , a content provider attempts to cloak the real content from the view of the search engine . Semantic cloaking refers to differences in meaning between pages which have the effect of deceiving search engine ranking algorithms . In this paper , we propose an automated two-step method to detect semantic cloaking pages based on different copies of the same page downloaded by a web crawler and a web browser . The first step is a filtering step , which generates a candidate list of semantic cloaking pages . In the second step , a classifier is used to detect semantic cloaking pages from the candidates generated by the filtering step . Experiments on manually labeled data sets show that we can generate a classifier with a precision of 93 % and a recall of 85 % . We apply our approach to links from the dmoz Open Directory Project and estimate that more than 50,000 of these pages employ semantic cloaking .

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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
spam
web search engine


Combining link and content analysis to estimate semantic similarity Search engines use content and link information to crawl , index , retrieve , and rank Web pages . The correlations between similarity measures based on these cues and on semantic associations between pages therefore crucially affects the performance of any search tool . Here I begin to quantitatively analyze the relationship between content , link , and semantic similarity measures across a massive number of Web page pairs . Maps of semantic similarity across textual and link similarity highlight the potential and limitations of lexical and link analysis for relevance approximation , and provide us with a way to study whether and how text and link based measures should be combined .

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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
content and link similarity
information search and retrieval
precision
recall
semantic maps
web search


Google news personalization : scalable online collaborative filtering Several approaches to collaborative filtering have been studied but seldom have studies been reported for large ( several millionusers and items ) and dynamic ( the underlying item set is continually changing ) settings . In this paper we describe our approach to collaborative filtering for generating personalized recommendations for users of Google News . We generate recommendations using three approaches : collaborative filtering using MinHash clustering , Probabilistic Latent Semantic Indexing ( PLSI ) , and covisitation counts . We combine recommendations from different algorithms using a linear model . Our approach is content agnostic and consequently domain independent , making it easily adaptable for other applications and languages with minimal effort . This paper will describe our algorithms and system setup in detail , and report results of running the recommendations engine on Google News .

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 B I 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 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

google news
minhash
personalization
plsi

mapreduce
miscellaneous
oneline recommendation system
scalable collaborative filtering


Evaluating the effectiveness of search task trails In this paper , we introduce `` task trail '' as a new concept to understand user search behaviors . We define task to be an atomic user information need . Web search logs have been studied mainly at session or query level where users may submit several queries within one task and handle several tasks within one session . Although previous studies have addressed the problem of task identification , little is known about the advantage of using task over session and query for search applications . In this paper , we conduct extensive analyses and comparisons to evaluate the effectiveness of task trails in three search applications : determining user satisfaction , predicting user search interests , and query suggestion . Experiments are conducted on large scale datasets from a commercial search engine . Experimental results show that : ( 1 ) Sessions and queries are not as precise as tasks in determining user satisfaction . ( 2 ) Task trails provide higher web page utilities to users than other sources . ( 3 ) Tasks represent atomic user information needs , and therefore can preserve topic similarity between query pairs . ( 4 ) Task-based query suggestion can provide complementary results to other models . The findings in this paper verify the need to extract task trails from web search logs and suggest potential applications in search and recommendation systems .

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

information search and retrieval
log analysis
search log mining
task evaluation


Diversifying web search results Result diversity is a topic of great importance as more facets of queries are discovered and users expect to find their desired facets in the first page of the results . However , the underlying questions of how ` diversity ' interplays with ` quality ' and when preference should be given to one or both are not well-understood . In this work , we model the problem as expectation maximization and study the challenges of estimating the model parameters and reaching an equilibrium . One model parameter , for example , is correlations between pages which we estimate using textual contents of pages and click data ( when available ) . We conduct experiments on diversifying randomly selected queries from a query log and the queries chosen from the disambiguation topics of Wikipedia . Our algorithm improves upon Google in terms of the diversity of random queries , retrieving 14 % to 38 % more aspects of queries in top 5 , while maintaining a precision very close to Google . On a more selective set of queries that are expected to benefit from diversification , our algorithm improves upon Google in terms of precision and diversity of the results , and significantly outperforms another baseline system for result diversification .

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

information search and retrieval
query ambiguity
search diversity


Using OWL for querying an XML\/RDF syntax Some recent initiatives try to take profit from RDF to make XML documents interoperate at the semantic level . Ontologies are used to establish semantic connections among XML languages , and some mechanisms have been defined to query them with natural XML query languages like XPath and XML Query . Generally structure-mapping approaches define a simple translation between trivial XPath expressions and some RDF query language like RDQL ; however some XPath constructs can not be covered in a structure-mapping strategy . In contrast , our work takes the model-mapping approach , respectful with node order , that allows mapping all XPath axis . The obtained XPath implementation has the properties of schema-awareness and IDREF-awareness , so it can be used to exploit inheritance hierarchies defined in one or more XML schemas .

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

idref-awareness
interoperability
schema-awareness
semantic integration


An evaluation of binary xml encoding optimizations for fast stream based xml processing This paper provides an objective evaluation of the performance impacts of binary XML encodings , using a fast stream-based XQuery processor as our representative application . Instead of proposing one binary format and comparing it against standard XML parsers , we investigate the individual effects of several binary encoding techniques that are shared by many proposals . Our goal is to provide a deeper understanding of the performance impacts of binary XML encodings in order to clarify the ongoing and often contentious debate over their merits , particularly in the domain of high performance XML stream processing .

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

performance evaluation
xml binary formats
xpath processing


Learning multiple graphs for document recommendations The Web offers rich relational data with different semantics . In this paper , we address the problem of document recommendation in a digital library , where the documents in question are networked by citations and are associated with other entities by various relations . Due to the sparsity of a single graph and noise in graph construction , we propose a new method for combining multiple graphs to measure document similarities , where different factorization strategies are used based on the nature of different graphs . In particular , the new method seeks a single low-dimensional embedding of documents that captures their relative similarities in a latent space . Based on the obtained embedding , a new recommendation framework is developed using semi-supervised learning on graphs . In addition , we address the scalability issue and propose an incremental algorithm . The new incremental method significantly improves the efficiency by calculating the embedding for new incoming documents only . The new batch and incremental methods are evaluated on two real world datasets prepared from CiteSeer . Experiments demonstrate significant quality improvement for our batch method and significant efficiency improvement with tolerable quality loss for our incremental method .

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

collaborative filtering
optimization
recommender systems
semi-supervised learning
social network analysis
spectral clustering


The webgraph framework I : compression techniques Studying web graphs is often difficult due to their large size . Recently , several proposals have been published about various techniques that allow tostore a web graph in memory in a limited space , exploiting the inner redundancies of the web . The WebGraph framework is a suite of codes , algorithms and tools that aims at making it easy to manipulate large web graphs . This papers presents the compression techniques used in WebGraph , which are centred around referentiation and intervalisation ( which in turn are dual to each other ) . WebGraph can compress the WebBase graph ( 118 Mnodes , 1 Glinks ) in as little as 3.08 bits per link , and its transposed version in as littleas 2.89 bits per link .

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 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 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


Online feedback by tests and reporting for elearning and certification programs The evaluation of eLearning success is an indispensable business requirement of education programs : the easy registration of ` visits ' to eLearning websites is , however , not sufficient in most cases . Additional metrics from authenticated logins and reports of learning activity and success - as obtained from specific online tests ' are required . The aim is to document the acceptance , progress and return of investment ( ROI ) of eLearning programs , and set up additional training well tailored to the needs of a specific learning community . An example from a corporate certification program proves the applicability of the proposed processes .

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


Thresher : automating the unwrapping of semantic content from the World Wide Web We describe Thresher , a system that lets non-technical users teach their browsers how to extract semantic web content from HTML documents on the World Wide Web . Users specify examples of semantic content by highlighting them in a web browser and describing their meaning . We then use the tree edit distance between the DOM subtrees of these examples to create a general pattern , or wrapper , for the content , and allow the user to bind RDF classes and predicates to the nodes of these wrappers . By overlaying matches to these patterns on standard documents inside the Haystack semantic web browser , we enable a rich semantic interaction with existing web pages , `` unwrapping '' semantic data buried in the pages ' HTML . By allowing end-users to create , modify , and utilize their own patterns , we hope to speed adoption and use of the Semantic Web and its applications .

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

haystack
rdf
semantic web
tree edit distance

on-line information services
user interfaces
wrapper induction


Mining models of human activities from the web The ability to determine what day-to-day activity ( such as cooking pasta , taking a pill , or watching a video ) a person is performing is of interest in many application domains . A system that can do this requires models of the activities of interest , but model construction does not scale well : humans must specify low-level details , such as segmentation and feature selection of sensor data , and high-level structure , such as spatio-temporal relations between states of the model , for each and every activity . As a result , previous practical activity recognition systems have been content to model a tiny fraction of the thousands of human activities that are potentially useful to detect . In this paper , we present an approach to sensing and modeling activities that scales to a much larger class of activities than before . We show how a new class of sensors , based on Radio Frequency Identification ( RFID ) tags , can directly yield semantic terms that describe the state of the physical world . These sensors allow us to formulate activity models by translating labeled activities , such as ` cooking pasta ' , into probabilistic collections of object terms , such as ` pot ' . Given this view of activity models as text translations , we show how to mine definitions of activities in an unsupervised manner from the web . We have used our technique to mine definitions for over 20,000 activities . We experimentally validate our approach using data gathered from actual human activity as well as simulated 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B 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


A scalable application placement controller for enterprise data centers Given a set of machines and a set of Web applications with dynamically changing demands , an online application placement controller decides how many instances to run for each application and where to put them , while observing all kinds of resource constraints . This NP hard problem has real usage in commercial middleware products . Existing approximation algorithms for this problem can scale to at most a few hundred machines , and may produce placement solutions that are far from optimal when system resources are tight . In this paper , we propose a new algorithm that can produce within 30seconds high-quality solutions for hard placement problems with thousands of machines and thousands of applications . This scalability is crucial for dynamic resource provisioning in large-scale enterprise data centers . Our algorithm allows multiple applications to share a single machine , and strivesto maximize the total satisfied application demand , to minimize the number of application starts and stops , and to balance the load across machines . Compared with existing state-of-the-art algorithms , for systems with 100 machines or less , our algorithm is up to 134 times faster , reduces application starts and stops by up to 97 % , and produces placement solutions that satisfy up to 25 % more application demands . Our algorithm has been implemented and adopted in a leading commercial middleware product for managing the performance of Web applications .

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 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


Analysis of community structure in Wikipedia We present the results of a community detection analysis of the Wikipedia graph . Distinct communities in Wikipedia contain semantically closely related articles . The central topic of a community can be identified using PageRank . Extracted communities can be organized hierarchically similar to manually created Wikipedia category structure .

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


A measurement-driven analysis of information propagation in the flickr social network Online social networking sites like MySpace , Facebook , and Flickr have become a popular way to share and disseminate content . Their massive popularity has led to viral marketing techniques that attempt to spread content , products , and ideas on these sites . However , there is little data publicly available on viral propagation in the real world and few studies have characterized how information spreads over current online social networks . In this paper , we collect and analyze large-scale traces of information dissemination in the Flickr social network . Our analysis , based on crawls of the favorite markings of 2.5 million users on 11 million photos , aims at answering three key questions : ( a ) how widely does information propagate in the social network ? ( b ) how quickly does information propagate ? and ( c ) what is the role of word-of-mouth exchanges between friends in the overall propagation of information in the network ? Contrary to viral marketing `` intuition , '' we find that ( a ) even popular photos do not spread widely throughout the network , ( b ) even popular photos spread slowly through the network , and ( c ) information exchanged between friends is likely to account for over 50 of all favorite-markings , but with a significant delay at each hop .

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

flickr
information dissemination
social networks
viral marketing


WebQuilt : a framework for capturing and visualizing the web experience

log file analysis
usability evaluation
web proxy
web visualization


A decentralized CF approach based on cooperative agents In this paper , we propose a decentralized collaborative filtering ( CF ) approach based on P2P overlay network for the autonomous agents ' environment . Experiments show that our approach is more scalable than traditional centralized CF filtering systems and alleviates the sparsity problem in distributed CF.

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

distributed collaborative filtering
friend network
p2p system


Understanding task-driven information flow in collaborative networks Collaborative networks are a special type of social network formed by members who collectively achieve specific goals , such as fixing software bugs and resolving customers ' problems . In such networks , information flow among members is driven by the tasks assigned to the network , and by the expertise of its members to complete those tasks . In this work , we analyze real-life collaborative networks to understand their common characteristics and how information is routed in these networks . Our study shows that collaborative networks exhibit significantly different properties compared with other complex networks . Collaborative networks have truncated power-law node degree distributions and other organizational constraints . Furthermore , the number of steps along which information is routed follows a truncated power-law distribution . Based on these observations , we developed a network model that can generate synthetic collaborative networks subject to certain structure constraints . Moreover , we developed a routing model that emulates task-driven information routing conducted by human beings in a collaborative network . Together , these two models can be used to study the efficiency of information routing for different types of collaborative networks -- a problem that is important in practice yet difficult to solve without the method proposed in this paper .

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 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 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


Do not crawl in the DUST : different URLs with similar text We consider the problem of dust : Different URLs with Similar Text . Such duplicate URLs are prevalent in web sites , as web server software often uses aliases and redirections , translates URLs to some canonical form , and dynamically generates the same page from various different URL requests . We present a novel algorithm , DustBuster , for uncovering dust ; that is , for discovering rules for transforming a given URL to others that are likely to have similar content . DustBuster is able to detect dust effectively from previous crawl logs or web server logs , without examining page contents . Verifying these rules via sampling requires fetching few actual web pages . Search engines can benefit from this information to increase the effectiveness of crawling , reduce indexing overhead as well as improve the quality of popularity statistics such as 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 B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


The recurrence dynamics of social tagging How often do tags recur ? How hard is predicting tag recurrence ? What tags are likely to recur ? We try to answer these questions by analyzing the RSDC08 dataset , in both individual and collective settings . Our findings provide useful insights for the development of tag suggestion techniques etc. .

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

content analysis and indexing
folksonomy
web 2.0


Web projections : learning from contextual subgraphs of the web Graphical relationships among Web pages have been exploited inmethods for ranking search results . To date , specific graphicalproperties have been used in these analyses . We introduce a WebProjection methodology that generalizes prior efforts of graphicalrelationships of the web in several ways . With the approach , wecreate subgraphs by projecting sets of pages and domains onto thelarger web graph , and then use machine learning to constructpredictive models that consider graphical properties as evidence . Wedescribe the method and then present experiments that illustrate theconstruction of predictive models of search result quality and userquery reformulation .

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

contextual subgraph
query reformulation
web projection
web search


ARROW : GenerAting SignatuRes to Detect DRive-By DOWnloads A drive-by download attack occurs when a user visits a webpage which attempts to automatically download malware without the user 's consent . Attackers sometimes use a malware distribution network ( MDN ) to manage a large number of malicious webpages , exploits , and malware executables . In this paper , we provide a new method to determine these MDNs from the secondary URLs and redirect chains recorded by a high-interaction client honeypot . In addition , we propose a novel drive-by download detection method . Instead of depending on the malicious content used by previous methods , our algorithm first identifies and then leverages the URLs of the MDN 's central servers , where a central server is a common server shared by a large percentage of the drive-by download attacks in the same MDN . A set of regular expression-based signatures are then generated based on the URLs of each central server . This method allows additional malicious webpages to be identified which launched but failed to execute a successful drive-by download attack . The new drive-by detection system named ARROW has been implemented , and we provide a large-scale evaluation on the output of a production drive-by detection system . The experimental results demonstrate the effectiveness of our method , where the detection coverage has been boosted by 96 % with an extremely low false positive rate .

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

drive-by download
invasive software
signature generation


Graphical representation of RDF queries In this poster we discuss a graphical notation for representing queries for semistructured data . We try to strike a balance between expressiveness of the query language and simplicity and understandability of the graphical notation . We present the primitives of the notation by means of examples .

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


Navigating the intranet with high precision Despite the success of web search engines , search over large enterprise intranets still suffers from poor result quality . Earlier work ( 6 ) that compared intranets and the Internet from the view point of keyword search has pointed to several reasons why the search problem is quite different in these two domains . In this paper , we address the problem of providing high quality answers to navigational queries in the intranet ( e.g. , queries intended to find product or personal home pages , service pages , etc. ) . Our approach is based on offline identification of navigational pages , intelligent generation of term-variants to associate with each page , and the construction of separate indices exclusively devoted to answering navigational queries . Using a testbed of 5.5 M pages from the IBM intranet , we present evaluation results that demonstrate that for navigational queries , our approach of using custom indices produces results of significantly higher precision than those produced by a general purpose search algorithm .

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

enterprise search
high precision information retrieval
information search and retrieval
intranet search


Web-scale entity-relation search architecture Enabling entity search and ranking at Web-scale is fraught with many challenges : annotating the corpus with entities and types , query language design , index design , query processing logic , and answer consolidation . We describe a Web-scale entity search engine we are building to handle over a billion Web pages , over 200,000 types , over 1,500,000 entities , and hundreds of entity annotations per page . We describe the design of compressed , token span oriented indices for entity and type annotations . Our prototype demonstrates the practicality of Web-scale entity-relation search .

O O O O O 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

entity-relation search
information search and retrieval
systems and software
web-scale


Constructing folksonomies by integrating structured metadata Aggregating many personal hierarchies into a common taxonomy , also known as a folksonomy , presents several challenges due to its sparseness , ambiguity , noise , and inconsistency . We describe an approach to folksonomy learning based on relational clustering that addresses these challenges by exploiting structured metadata contained in personal hierarchies . Our approach clusters similar hierarchies using their structure and tag statistics , then incrementally weaves them into a deeper , bushier tree . We study folksonomy learning using social metadata extracted from the photo-sharing site Flickr . We evaluate the learned folksonomy quantitatively by automatically comparing it to a reference taxonomy created by the Open Directory Project . Our empirical results suggest that the proposed approach improves upon the state-of-the-art folksonomy learning method .

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


Enhancing web search with entity intent Web entities , such as documents and hyperlinks , are created for different purposes , or intents . Existing intent-based retrieval methods largely focus on information seekers ' intent expressed by queries , ignoring the other side of the problem : web content creators ' intent . We argue that understanding why the content was created is also important . In this work , we propose to classify such intents into two broad categories : `` navigational '' and `` informational '' . Then we incorporate such intents into traditional retrieval models , and show their effect on ranking performance .

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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
query intent
retrieval model
web entity intent


Here , there , and everywhere : correlated online behaviors can lead to overestimates of the effects of advertising Measuring the causal effects of online advertising ( adfx ) on user behavior is important to the health of the WWW publishing industry . In this paper , using three controlled experiments , we show that observational data frequently lead to incorrect estimates of adfx . The reason , which we label `` activity bias , '' comes from the surprising amount of time-based correlation between the myriad activities that users undertake online . In Experiment 1 , users who are exposed to an ad on a given day are much more likely to engage in brand-relevant search queries as compared to their recent history for reasons that had nothing do with the advertisement . In Experiment 2 , we show that activity bias occurs for page views across diverse websites . In Experiment 3 , we track account sign-ups at a competitor 's ( of the advertiser ) website and find that many more people sign-up on the day they saw an advertisement than on other days , but that the true `` competitive effect '' was minimal . In all three experiments , exposure to a campaign signals doing `` more of everything '' in given period of time , making it difficult to find a suitable `` matched control '' using prior behavior . In such cases , the `` match '' is fundamentally different from the exposed group , and we show how and why observational methods lead to a massive overestimate of adfx in such circumstances .

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

advertising effectiveness
browsing behavior
causal inference
field experiments
selection bias


Merkle tree authentication of HTTP responses We propose extensions to existing web protocols that allow proofs of authenticity of HTTP server responses , whether or not the HTTP server is under the control of the publisher . These extensions protect users from content that may be substituted by malicious servers , and therefore have immediate applications in improving the security of web caching , mirroring , and relaying systems that rely on untrusted machines ( 2,4 ) . Our proposal relies on Merkle trees to support 200 and 404 response authentication while requiring only a single cryptographic hash of trusted data per repository . While existing web protocols such as HTTPS can provide authenticity guarantees ( in addition to confidentiality ) , HTTPS consumes significantly more computational resources , and requires that the hosting server act without malice in generating responses and in protecting the publisher 's private key .

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 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

merkle hash tree
web content distribution


Distributed location aware web crawling Distributed crawling has shown that it can overcome important limitations of the today 's crawling paradigm . However , the optimal benefits of this approach are usually limited to the sites hosting the crawler . In this work , we propose a location-aware method , called IPMicra , that utilizes an IP address hierarchy , and allows crawling of links in a near optimal location aware manner .

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


Echoes of power : language effects and power differences in social interaction Understanding social interaction within groups is key to analyzing online communities . Most current work focuses on structural properties : who talks to whom , and how such interactions form larger network structures . The interactions themselves , however , generally take place in the form of natural language -- either spoken or written -- and one could reasonably suppose that signals manifested in language might also provide information about roles , status , and other aspects of the group 's dynamics . To date , however , finding domain-independent language-based signals has been a challenge . Here , we show that in group discussions , power differentials between participants are subtly revealed by how much one individual immediately echoes the linguistic style of the person they are responding to . Starting from this observation , we propose an analysis framework based on linguistic coordination that can be used to shed light on power relationships and that works consistently across multiple types of power -- including a more `` static '' form of power based on status differences , and a more `` situational '' form of power in which one individual experiences a type of dependence on another . Using this framework , we study how conversational behavior can reveal power relationships in two very different settings : discussions among Wikipedians and arguments before the U. S. Supreme Court .

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

coordination
dependence
language
linguistic style
online communities
power

accommodation
linguistic convergence
relations
social and behavioral sciences
social status


An integrated method for social network extraction A social network can become bases for information infrastructure in the future . It is important to extract social networks that are not biased . Providing a simple means for users to register their social relation is also important . We propose a method that combines various approaches to extract social networks . Especially , three kinds of networks are extracted ; user-registered Know link network , Web-mined Web link network , and face-to-face Touch link network . In this paper , the combination of social network extraction for communities is described , and the analysis on the extracted social networks is shown .

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

miscellaneous
user interaction
web mining


Talking about data : sharing richly structured information through blogs and wikis The web has dramatically enhanced people 's ability to communicate ideas , knowledge , and opinions . But the authoring tools that most people understand , blogs and wikis , primarily guide users toward authoring text . In this work , we show that substantial gains in expressivity and communication would accrue if people could easily share richly structured information in meaningful visualizations . We then describe several extensions we have created for blogs and wikis that enable users to publish , share , and aggregate such structured information using the same workflows they apply to text . In particular , we aim to preserve those attributes that make blogs and wikis so effective : one-click access to the information , one-click publishing of content , natural authoring interfaces , and the ability to easily copy-and-paste information and visualizations from other sources .

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 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 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 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


Optimal rare query suggestion with implicit user feedback Query suggestion has been an effective approach to help users narrow down to the information they need . However , most of existing studies focused on only popular\/head queries . Since rare queries possess much less information ( e.g. , clicks ) than popular queries in the query logs , it is much more difficult to efficiently suggest relevant queries to a rare query . In this paper , we propose an optimal rare query suggestion framework by leveraging implicit feedbacks from users in the query logs . Our model resembles the principle of pseudo-relevance feedback which assumes that top-returned results by search engines are relevant . However , we argue that the clicked URLs and skipped URLs contain different levels of information and thus should be treated differently . Hence , our framework optimally combines both the click and skip information from users and uses a random walk model to optimize the query correlation . Our model specifically optimizes two parameters : ( 1 ) the restarting ( jumping ) rate of random walk , and ( 2 ) the combination ratio of click and skip information . Unlike the Rocchio algorithm , our learning process does not involve the content of the URLs but simply leverages the click and skip counts in the query-URL bipartite graphs . Consequently , our model is capable of scaling up to the need of commercial search engines . Experimental results on one-month query logs from a large commercial search engine with over 40 million rare queries demonstrate the superiority of our framework , with statistical significance , over the traditional random walk models and pseudo-relevance feedback models .

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


Abstracting application-level web security Application-level web security refers to vulnerabilities inherent in the code of a web-application itself ( irrespective of the technologies in which it is implemented or the security of the web-server\/back-end database on which it is built ) . In the last few months application-level vulnerabilities have been exploited with serious consequences : hackers have tricked e-commerce sites into shipping goods for no charge , user-names and passwords have been harvested and condential information ( such as addresses and credit-card numbers ) has been leaked . In this paper we investigate new tools and techniques which address the problem of application-level web security . We ( i ) describe a scalable structuring mechanism facilitating the abstraction of security policies from large web-applications developed in heterogenous multi-platform environments ; ( ii ) present a tool which assists programmers develop secure applications which are resilient to a wide range of common attacks ; and ( iii ) report results and experience arising from our implementation of these techniques .

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

application-level web security
component-based design
security policy description language


Hybrid keyword search auctions Search auctions have become a dominant source of revenue generation on the Internet . Such auctions have typically used per-click bidding and pricing . We propose the use of hybrid auctions where an advertiser can make a per-impression as well as a per-click bid , and the auctioneer then chooses one of the two as the pricing mechanism . We assume that the advertiser and the auctioneer both have separate beliefs ( called priors ) on the click-probability of an advertisement . We first prove that the hybrid auction is truthful , assuming that the advertisers are risk-neutral . We then show that this auction is superior to the existing per-click auction in multiple ways : We show that risk-seeking advertisers will choose only a per-impression bid whereas risk-averse advertisers will choose only a per-click bid , and argue that both kind of advertisers arise naturally . Hence , the ability to bid in a hybrid fashion is important to account for the risk characteristics of the advertisers . For obscure keywords , the auctioneer is unlikely to have a very sharp prior on the click-probabilities . In such situations , we show that having the extra information from the advertisers in the form of a per-impression bid can result in significantly higher revenue . An advertiser who believes that its click-probability is much higher than the auctioneer 's estimate can use per-impression bids to correct the auctioneer 's prior without incurring any extra cost . The hybrid auction can allow the advertiser and auctioneer to implement complex dynamic programming strategies to deal with the uncertainty in the click-probability using the same basic auction . The per-click and per-impression bidding schemes can only be used to implement two extreme cases of these strategies . As Internet commerce matures , we need more sophisticated pricing models to exploit all the information held by each of the participants . We believe that hybrid auctions could be an important step in this direction . The hybrid auction easily extends to multiple slots , and is also applicable to scenarios where the hybrid bidding is per-impression and per-action ( i.e. CPM and CPA ) , or per-click and per-action ( i.e. CPC and CPA ) .

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

keyword auctions
mechanism design
nonnumerical algorithms and problems


Measuring a commercial content delivery network Content delivery networks ( CDNs ) have become a crucial part of the modern Web infrastructure . This paper studies the performance of the leading content delivery provider - Akamai . It measures the performance of the current Akamai platform and considers a key architectural question faced by both CDN designers and their prospective customers : whether the co-location approach to CDN platforms adopted by Akamai , which tries to deploy servers in numerous Internet locations , brings inherent performance benefits over a more consolidated data center approach pursued by other influential CDNs such as Limelight . We believe the methodology we developed for this study will be useful for other researchers in the CDN arena .

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


Combining global optimization with local selection for efficient QoS-aware service composition The run-time binding of web services has been recently put forward in order to support rapid and dynamic web service compositions . With the growing number of alternative web services that provide the same functionality but differ in quality parameters , the service composition becomes a decision problem on which component services should be selected such that user 's end-to-end QoS requirements ( e.g. availability , response time ) and preferences ( e.g. price ) are satisfied . Although very efficient , local selection strategy fails short in handling global QoS requirements . Solutions based on global optimization , on the other hand , can handle global constraints , but their poor performance renders them inappropriate for applications with dynamic and real-time requirements . In this paper we address this problem and propose a solution that combines global optimization with local selection techniques to benefit from the advantages of both worlds . The proposed solution consists of two steps : first , we use mixed integer programming ( MIP ) to find the optimal decomposition of global QoS constraints into local constraints . Second , we use distributed local selection to find the best web services that satisfy these local constraints . The results of experimental evaluation indicate that our approach significantly outperforms existing solutions in terms of computation time while achieving close-to-optimal results .

O O B O O 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 B I 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 B 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 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 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

optimization
qos
service composition
web services


Intelligent crawling on the World Wide Web with arbitrary predicates


Beyond XML and RDF : the versatile web query language xcerpt Applications and services that access Web data are becoming increasingly more useful and wide-spread . Current main-stream Web query languages such as XQuery , XSLT , or SPARQL , however , focus only on one of the different data formats available on the Web . In contrast , Xcerpt is a emphversatile semi-structured query language , i.e. , a query language able to access all kinds of Web data such as XML and RDF in the same language reusing common concepts and language constructs . To integrate heterogeneous data and as a foundation for Semantic Web reasoning , Xcerpt also provides rules . Xcerpt has a visual companion language , visXcerpt , that is conceived as a mere rendering of the ( textual ) query language Xcerpt using a slightly extended CSS . Both languages are demonstrated along a realistic use case integrating XML and RDF data highlighting interesting and unique features . Novel language constructs and optimization techniques are currently under investigation in the Xcerpt project ( cf. @ urlhttp : \/ \/ xcerpt.org \/ ) .

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


Investigating behavioral variability in web search Understanding the extent to which people 's search behaviors differ in terms of the interaction flow and information targeted is important in designing interfaces to help World Wide Web users search more effectively . In this paper we describe a longitudinal log-based study that investigated variability in people . s interaction behavior when engaged in search-related activities on the Web . allWe analyze the search interactions of more than two thousand volunteer users over a five-month period , with the aim of characterizing differences in their interaction styles . allThe findings of our study suggest that there are dramatic differences in variability in key aspects of the interaction within and between users , and within and between the search queries they submit . allOur findings also suggest two classes of extreme user . navigators and explorers . whose search interaction is highly consistent or highly variable . Lessons learned from these users can inform the design of tools to support effective Web-search interactions for everyone .

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


A combined approach to checking web ontologies The understanding of Semantic Web documents is built upon ontologies that define concepts and relationships of data . Hence , the correctness of ontologies is vital . Ontology reasoners such as RACER and FaCT have been developed to reason ontologies with a high degree of automation . However , complex ontology-related properties may not be expressible within the current web ontology languages , consequently they may not be checkable by RACER and FaCT . We propose to use the software engineering techniques and tools , i.e. , Z\/EVES and Alloy Analyzer , to complement the ontology tools for checking Semantic Web documents . In this approach , Z\/EVES is first applied to remove trivial syntax and type errors of the ontologies . Next , RACER is used to identify any ontological inconsistencies , whose origins can be traced by Alloy Analyzer . Finally Z\/EVES is used again to express complex ontology-related properties and reveal errors beyond the modeling capabilities of the current web ontology languages . We have successfully applied this approach to checking a set of military plan ontologies .

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


Budget constrained bidding in keyword auctions and online knapsack problems We consider the budget-constrained bidding optimization problem for sponsored search auctions , and model it as an online ( multiple-choice ) knapsack problem . We design both deterministic and randomized algorithms for the online ( multiple-choice ) knapsack problems achieving a provably optimal competitive ratio . This translates back to fully automatic bidding strategies maximizing either profit or revenue for the budget-constrained advertiser . Our bidding strategy for revenue maximization is oblivious ( i.e. , without knowledge ) of other bidders ' prices and\/or click-through-rates for those positions . We evaluate our bidding algorithms using both synthetic data and real bidding data gathered manually , and also discuss a sniping heuristic that strictly improves bidding performance . With sniping and parameter tuning enabled , our bidding algorithms can achieve a performance ratio above 90 % against the optimum by the omniscient bidder .

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

keyword bidding
multiple-choice knapsack problem
online knapsack problem
sponsored search auction


Fine grained access control for SOAP E-services

certificates
internet
roles
security and protection
standards
xml


Enhancing the SCORM metadata model Nowadays , the leading e-learning platforms are converging towards standardization . This paper presents an extension to the SCORM , today 's most well acclaimed e-learning standard , enabling the modelling of course related entities that surround learning objects and content aggregations , therefore increasing the standard 's modelling scope and allowing for gains in efficiency in knowledge dissemination . A prototype is being implemented and tested on VIANET , an original e-learning platform with extensible support for the SCORM . content aggregations .

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


Generalized fact-finding Once information retrieval has located a document , and information extraction has provided its contents , how do we know whether we should actually believe it ? Fact-finders are a state-of-the-art class of algorithms that operate in a manner analogous to Kleinberg 's Hubs and Authorities , iteratively computing the trustworthiness of an information source as a function of the believability of the claims it makes , and the believability of a claim as a function of the trustworthiness of those sources asserting it . However , as fact-finders consider only `` who claims what '' , they ignore a great deal of relevant background and contextual information . We present a framework for `` lifting '' ( generalizing ) the fact-finding process , allowing us to elegantly incorporate knowledge such as the confidence of the information extractor and the attributes of the information sources . Experiments demonstrate that leveraging this information significantly improves performance over existing , `` unlifted '' fact-finding 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 integration
fact-finders
graph algorithms
trust


The anatomy of a news search engine Today , news browsing and searching is one of the most important Internet activity . This paper introduces a general framework to build a News search engine by describing Velthune , an academic News search engine available on line .

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

extraction
information
information search and retrieval
news search engines
syndication


Towards semantic knowledge propagation from text corpus to web images In this paper , we study the problem of transfer learning from text to images in the context of network data in which link based bridges are available to transfer the knowledge between the different domains . The problem of classification of image data is often much more challenging than text data because of the following two reasons : ( a ) Labeled text data is very widely available for classification purposes . On the other hand , this is often not the case for image data , in which a lot of images are available from many sources , but many of them are often not labeled . ( b ) The image features are not directly related to semantic concepts inherent in class labels . On the other hand , since text data tends to have natural semantic interpretability ( because of their human origins ) , they are often more directly related to class labels . Therefore , the relationships between the images and text features also provide additional hints for the classification process in terms of the image feature transformations which provide the most effective results . The semantic challenges of image features are glaringly evident , when we attempt to recognize complex abstract concepts , and the visual features often fail to discriminate such concepts . However , the copious availability of bridging relationships between text and images in the context of web and social network data can be used in order to design for effective classifiers for image data . One of our goals in this paper is to develop a mathematical model for the functional relationships between text and image features , so as indirectly transfer semantic knowledge through feature transformations . This feature transformation is accomplished by mapping instances from different domains into a common space of unspecific topics . This is used as a bridge to semantically connect the two heterogeneous spaces . This is also helpful for the cases where little image data is available for the classification process . We evaluate our knowledge transfer techniques on an image classification task with labeled text corpora and show the effectiveness with respect to competing 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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-domain label propagation
heterogeneous knowledge propagation
text corpus and web images
translator function


Multispace information visualization framework for the intercomparison of data sets retrieved from web services We introduce a new visualization framework for the intercomparison of more than one data set retrieved from Web services . In our framework , we use more than one visualization space simultaneously , each of which visualizes a single data set retrieved from the Web service . For this purpose , we provide a new 3D component for accessing Web services , and provide a 3D space component , in which data set retrieved from the Web service is visualized . Moreover , our framework provides users with various operations applicable to these space components , i.e. , union , intersection , set-difference , cross-product , selection , projection , and joins .

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

graphical user interfaces
intelligentbox
interaction styles
worldbottle


Image classification for mobile web browsing It is difficult for users of mobile devices such as cellular phones equipped with a small screen and a poor input interface to browse Web pages designed for desktop PCs with large displays . Many studies and commercial products have tried to solve this problem . Web pages include images that have various roles such as site menus , line headers for itemization , and page titles . However , most studies of mobile Web browsing have n't paid much attention to the roles of Web images . In this paper , we define eleven Web image categories according to their roles and use these categories for proper Web image handling . We manually categorized 3,901 Web images collected from forty Web sites and extracted image features of each category according to the classification . By making use of the extracted features , we devised an automatic Web image classification method . Furthermore , we evaluated the automatic classification of real Web pages and achieved up to 83.1 % classification accuracy . We also implemented an automatic Web page scrolling system as an application of our automatic image classification method .

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 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 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


Tag ranking Social media sharing web sites like Flickr allow users to annotate images with free tags , which significantly facilitate Web image search and organization . However , the tags associated with an image generally are in a random order without any importance or relevance information , which limits the effectiveness of these tags in search and other applications . In this paper , we propose a tag ranking scheme , aiming to automatically rank the tags associated with a given image according to their relevance to the image content . We first estimate initial relevance scores for the tags based on probability density estimation , and then perform a random walk over a tag similarity graph to refine the relevance scores . Experimental results on a 50 , 000 Flickr photo collection show that the proposed tag ranking method is both effective and efficient . We also apply tag ranking into three applications : ( 1 ) tag-based image search , ( 2 ) tag recommendation , and ( 3 ) group recommendation , which demonstrates that the proposed tag ranking approach really boosts the performances of social-tagging related applications .

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

flickr
random walk
recommendation
search
tag ranking