Hierarchical location and topic based query expansion

Shu Huang, Qiankun Zhao, Prasenjit Mitra, C. Lee Giles

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

In this paper, we propose a novel approach to expand queries by exploring both location information and topic information of the queries. Users at different locations tend to have different vocabularies, while the different expressions coming from different vocabularies may relate to the same topics. Thus these expressions are identified as location sensitive and can be used for query expansion. We propose a hierarchical query expansion model, which employs a two-level SVM classification model to classify queries as location sensitive or location non-sensitive, where the former are further classified into same location sensitive and different location sensitive. For the location sensitive queries, we propose an LDA based topic-level query similarity measure to rank the list of similar queries. Experiments with 2G raw log data from CiteSeer and Excite1 show that our hierarchical classification model predicts the query location sensitivity with more than 80% precision and that the final search result is significantly better than existing query expansion methods.

Original languageEnglish (US)
Title of host publicationAAAI-08/IAAI-08 Proceedings - 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference
Pages1150-1155
Number of pages6
StatePublished - Dec 24 2008
Event23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference, AAAI-08/IAAI-08 - Chicago, IL, United States
Duration: Jul 13 2008Jul 17 2008

Publication series

NameProceedings of the National Conference on Artificial Intelligence
Volume2

Other

Other23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference, AAAI-08/IAAI-08
CountryUnited States
CityChicago, IL
Period7/13/087/17/08

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

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  • Cite this

    Huang, S., Zhao, Q., Mitra, P., & Giles, C. L. (2008). Hierarchical location and topic based query expansion. In AAAI-08/IAAI-08 Proceedings - 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference (pp. 1150-1155). (Proceedings of the National Conference on Artificial Intelligence; Vol. 2).