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Published in:
2007 | OriginalPaper | Chapter
Using Bloom Filters to Speed Up HITS-Like Ranking Algorithms
Authors : Sreenivas Gollapudi, Marc Najork, Rina Panigrahy
Published in: Algorithms and Models for the Web-Graph
Publisher: Springer Berlin Heidelberg
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This paper describes a technique for reducing the query-time cost of HITS-like ranking algorithm. The basic idea is to compute for each node in the web graph a summary of its immediate neighborhood (which is a query-independent operation and thus can be done off-line), and to approximate the neighborhood graph of a result set at query-time by combining the summaries of the result set nodes. This approximation of the query-specific neighborhood graph can then be used to perform query-dependent link-based ranking algorithms such as HITS and SALSA. We have evaluated our technique on a large web graph and a substantial set of queries with partially judged results, and found that its effectiveness (retrieval performance) is comparable to the original SALSA algorithm, while its efficiency (query-time speed) is substantially higher.