TY - GEN
T1 - Context-aware personalized search based on user and resource profiles in folksonomies
AU - Xie, Haoran
AU - Li, Qing
AU - Mao, Xudong
PY - 2012
Y1 - 2012
N2 - The explosion of collaborative tagging data nowadays prompts an urgent demand upon Web 2.0 communities in assisting users to search interested resources quickly and effectively. Such a requirement entails much research on utilization of tag-based user and resource profiles so as to provide a personalized search in folksonomies. However, one major shortage for existing methods is their uniform treatment of user profile in the same way for each query, hence the search context for each query is ignored. In this paper, we focus on addressing this problem by modeling the search context. To capture and understand user intention, a nested context model is proposed. Furthermore, we conduct the experimental evaluation upon a real life data set, and the experimental result demonstrates that our approach is more effective than baselines. © 2012 Springer-Verlag Berlin Heidelberg.
AB - The explosion of collaborative tagging data nowadays prompts an urgent demand upon Web 2.0 communities in assisting users to search interested resources quickly and effectively. Such a requirement entails much research on utilization of tag-based user and resource profiles so as to provide a personalized search in folksonomies. However, one major shortage for existing methods is their uniform treatment of user profile in the same way for each query, hence the search context for each query is ignored. In this paper, we focus on addressing this problem by modeling the search context. To capture and understand user intention, a nested context model is proposed. Furthermore, we conduct the experimental evaluation upon a real life data set, and the experimental result demonstrates that our approach is more effective than baselines. © 2012 Springer-Verlag Berlin Heidelberg.
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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84859705013&origin=recordpage
U2 - 10.1007/978-3-642-29253-8_9
DO - 10.1007/978-3-642-29253-8_9
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9783642292521
VL - 7235 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 97
EP - 108
BT - Web Technologies and Applications
PB - Springer Verlag
T2 - 14th Asia Pacific Web Technology Conference, APWeb 2012
Y2 - 11 April 2012 through 13 April 2012
ER -