TY - GEN
T1 - Excalibur
T2 - Proceedings of the 28th Annual International Computer Software and Applications Conference; Workshop Papers and Fast Abstracts, COMPSAC 2004
AU - Yuen, Leo
AU - Chang, Matthew
AU - Lai, Ying Kit
AU - Poon, Chung Keung
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 - 2004
Y1 - 2004
N2 - General purpose Web search engines are becoming ineffective due to the rapid growth and changes in the contents of the World Wide Web. Meta-search engines help a bit by having a better coverage of the WWW. However, users are still overwhelmed by the large amount of irrelevant results returned by a search. A promising approach to tackle the problem is personalized search. Thus the problem of capturing users' personal information need and re-organizing the results has attracted a lot of attention. In this paper, we present a meta-search engine that extracts users' preference implicitly and provides immediate response by re-ranking the results. Re-ranking is done by using the Naive Bayesian classifier and the resemblance measure. Moreover, we show that the users' preference can be succinctly represented by a few keywords. © 2004 IEEE.
AB - General purpose Web search engines are becoming ineffective due to the rapid growth and changes in the contents of the World Wide Web. Meta-search engines help a bit by having a better coverage of the WWW. However, users are still overwhelmed by the large amount of irrelevant results returned by a search. A promising approach to tackle the problem is personalized search. Thus the problem of capturing users' personal information need and re-organizing the results has attracted a lot of attention. In this paper, we present a meta-search engine that extracts users' preference implicitly and provides immediate response by re-ranking the results. Re-ranking is done by using the Naive Bayesian classifier and the resemblance measure. Moreover, we show that the users' preference can be succinctly represented by a few keywords. © 2004 IEEE.
UR - http://www.scopus.com/inward/record.url?scp=18844451537&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-18844451537&origin=recordpage
U2 - 10.1109/CMPSAC.2004.1342671
DO - 10.1109/CMPSAC.2004.1342671
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 0769522092
VL - 2
T3 - Proceedings - International Computer Software and Applications Conference
SP - 49
EP - 50
BT - Proceedings of the 28th Annual International Computer Software and Applications Conference; Workshop Papers and Fast Abstracts, COMPSAC 2004
Y2 - 28 September 2004 through 30 September 2004
ER -