Full Paper (8 pages)
Official ACM published version: http://doi.acm.org/10.1145/1390334.1390411
Author's copy: PDF (284KB)
Web pages, like people, are often known by others in a variety of contexts. When those contexts are sufficiently distinct, a page's importance may be better represented by multiple domains of authority, rather than by one that indiscriminately mixes reputations. In this work we determine domains of authority by examining the contexts in which a page is cited. However, we find that it is not enough to determine separate domains of authority; our model additionally determines the local flow of authority based upon the relative similarity of the source and target authority domains. In this way, we differentiate both incoming and outgoing hyperlinks by topicality and importance rather than treating them indiscriminately. We find that this approach compares favorably to other topical ranking methods on two real-world datasets and produces an approximately 10% improvement in precision and quality of the top ten results over PageRank.
In Proceedings of the 31st Annual International ACM SIGIR Conference on Research & Development on Information Retrieval, pages 443-450, Singapore, July 2008.
© ACM, 2008. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution.
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