STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
A decentralized algorithm for spectral analysis
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
An economic model of the worldwide web
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
Lexical and semantic clustering by web links
Journal of the American Society for Information Science and Technology - Special issue: Webometrics
Page quality: in search of an unbiased web ranking
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Core algorithms in the CLEVER system
ACM Transactions on Internet Technology (TOIT)
Associative search in peer to peer networks: Harnessing latent semantics
Computer Networks: The International Journal of Computer and Telecommunications Networking
Combining content and link for classification using matrix factorization
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
A decentralized algorithm for spectral analysis
Journal of Computer and System Sciences
Cluster Based Personalized Search
WAW '09 Proceedings of the 6th International Workshop on Algorithms and Models for the Web-Graph
Group-Level Analysis and Visualization of Social Networks
Algorithmics of Large and Complex Networks
Sensitivity and Stability of Ranking Vectors
SIAM Journal on Scientific Computing
Experiments with an economic model of the worldwide web
WINE'05 Proceedings of the First international conference on Internet and Network Economics
The compass filter: search engine result personalization using web communities
ITWP'03 Proceedings of the 2003 international conference on Intelligent Techniques for Web Personalization
Low rank approximation and regression in input sparsity time
Proceedings of the forty-fifth annual ACM symposium on Theory of computing
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We present a model for web search that captures in a unified manner three critical components of the problem: how the link structure of the web is generated, how the contentof a web document is generated, and how a human searcher generates a query. The key to this unification lies in capturing the correlations between these components in terms of proximity in a shared latent semantic space. Given such a combined model, the correct answer to a search query is well defined, and thus it becomes possible to evaluate web search algorithms rigorously. We present a new web search algorithm, based on spectral techniques, and prove that it is guaranteed to produce an approximately correct answer in our model. The algorithm assumes no knowledge of the model, and is well-defined regardless of the model's accuracy.