Matrix computations (3rd ed.)
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Authoritative sources in a hyperlinked environment
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
IR evaluation methods for retrieving highly relevant documents
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Does “authority” mean quality? predicting expert quality ratings of Web documents
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 11th international conference on World Wide Web
Modern Information Retrieval
Cumulated gain-based evaluation of IR techniques
ACM Transactions on Information Systems (TOIS)
Convex Optimization
ACM Transactions on Internet Technology (TOIT)
PageRank as a function of the damping factor
WWW '05 Proceedings of the 14th international conference on World Wide Web
A uniform approach to accelerated PageRank computation
WWW '05 Proceedings of the 14th international conference on World Wide Web
Usage-Based PageRank for Web Personalization
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Studying the use of popular destinations to enhance web search interaction
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Combating web spam with trustrank
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
BrowseRank: letting web users vote for page importance
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Comparison of two algorithms for computing page importance
AAIM'10 Proceedings of the 6th international conference on Algorithmic aspects in information and management
Time-weighted web authoritative ranking
Information Retrieval
ClickRank: Learning Session-Context Models to Enrich Web Search Ranking
ACM Transactions on the Web (TWEB)
Image ranking based on user browsing behavior
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Introducing search behavior into browsing based models of page's importance
Proceedings of the 22nd international conference on World Wide Web companion
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This paper is concerned with a framework to compute the importance of webpages by using real browsing behaviors of Web users. In contrast, many previous approaches like PageRank compute page importance through the use of the hyperlink graph of the Web. Recently, people have realized that the hyperlink graph is incomplete and inaccurate as a data source for determining page importance, and proposed using the real behaviors of Web users instead. In this paper, we propose a formal framework to compute page importance from user behavior data (which covers some previous works as special cases). First, we use a stochastic process to model the browsing behaviors of Web users. According to the analysis on hundreds of millions of real records of user behaviors, we justify that the process is actually a continuous-time time-homogeneous Markov process, and its stationary probability distribution can be used as the measure of page importance. Second, we propose a number of ways to estimate parameters of the stochastic process from real data, which result in a group of algorithms for page importance computation (all referred to as BrowseRank). Our experimental results have shown that the proposed algorithms can outperform the baseline methods such as PageRank and TrustRank in several tasks, demonstrating the advantage of using our proposed framework.