TY - GEN
T1 - Log mining to improve the performance of site search
AU - Xue, Gui-Rong
AU - Zeng, Hua-Jun
AU - Chen, Zheng
AU - Ma, Wei-Ying
AU - Lu, Chao-Jun
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2002
Y1 - 2002
N2 - 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 generalized 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. © 2002 IEEE.
AB - 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 generalized 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. © 2002 IEEE.
UR - https://www.scopus.com/pages/publications/84966963787
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84966963787&origin=recordpage
U2 - 10.1109/WISEW.2002.1177868
DO - 10.1109/WISEW.2002.1177868
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 0769518133
SN - 9780769518138
T3 - WISE 2002 - Proceedings of the 3rd International Conference on Web Information Systems Engineering Workshops
SP - 238
EP - 245
BT - WISE 2002 - Proceedings of the 3rd International Conference on Web Information Systems Engineering Workshops
PB - IEEE
T2 - 3rd International Conference on Web Information Systems Engineering Workshops, WISE 2002
Y2 - 11 December 2002
ER -