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Ranking the tens of thousands of retrieved webpages for a user query on a Web search engine such that the most informative webpages are on the top is a key information retrieval technology. A popular ranking algorithm is the HITS algorithm of Kleinberg. It explores the reinforcing interplay between authority and hub webpages on a particular topic by taking into account the structure of the Web graphs formed by the hyperlinks between the webpages. In this paper, we give a detailed analysis of the HITS algorithm through a unique combination of probabilistic analysis and matrix algebra. In particular, we show that to first-order approximation, theranking given by the HITS algorithm is the same as the ranking by counting inbound and outbound hyperlinks. Using Web graphs of different sizes, we also provide experimental results to illustrate the analysis.
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Ding et al. (2004) studied this question.
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