Research on PageRank and Hyperlink-Induced Topic Search in Web Structure Mining

A fast and efficient page ranking mechanism for web crawling and retrieval remains as a challenging issue. Recently, several link based ranking algorithms like PageRank and HITS have been proposed. To yield more accurate search results, we propose computing a set of PageRank vectors, biased using a set of representative topics, to capture more accurately the notion of importance with respect to a particular topic. Experiment results shows that the proposed algorithm increases the degree of relevance than the original one, and decreases the query time efforts of topic sensitive PageRank.