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2002
Springer

Log Mining to Improve the Performance of Site Search

9 years 4 months ago
Log Mining to Improve the Performance of Site Search
Despite of the popularity of global search engines, people still suffer from low accuracy of site search. The primary reason lies in the difference of link structures and data scale between global Web and website, which leads to failures of traditional re-ranking methods such as HITS, PageRank and DirectHit. This paper proposes a novel re-ranking method based on user logs within websites. With the help of website taxonomy, we mine for zed association rules and abstract access patterns of different levels. Mining results are subsequently used to re-rank the retrieved pages. One of the advantages of our mining algorithm is that it resolves the diversity problem of user’s access behavior and discovers general patterns. Experiment shows that the proposed method outperforms keyword-based method by 15% and DirectHit by 13% respectively.
Gui-Rong Xue, Hua-Jun Zeng, Zheng Chen, Wei-Ying M
Added 16 Jul 2010
Updated 16 Jul 2010
Type Conference
Year 2002
Where WISE
Authors Gui-Rong Xue, Hua-Jun Zeng, Zheng Chen, Wei-Ying Ma, Chao-Jun Lu
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