Improving identification of latent user goals through search-result snippet classification

Kuan Yu He, Yao Sheng Chang, Wen-Hsiang Lu

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

13 Citations (Scopus)

Abstract

In this paper, we propose an enhanced approach to improving our previous method which employs syntactic structures (verb-object pairs) to identify latent user goals. Our new approach employs a supervised-learning method to learn hint verbs and considers URL information and title information to classify snippets into three coarse categories, which are resource-seeking, informational, and navigational. Also, we propose three different models to identify three different categories of specific latent user goals from the classified snippets.

Original languageEnglish
Title of host publicationProceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007
Pages683-686
Number of pages4
DOIs
Publication statusPublished - 2007 Dec 1
EventIEEE/WIC/ACM International Conference on Web Intelligence, WI 2007 - Silicon Valley, CA, United States
Duration: 2007 Nov 22007 Nov 5

Publication series

NameProceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007

Other

OtherIEEE/WIC/ACM International Conference on Web Intelligence, WI 2007
CountryUnited States
CitySilicon Valley, CA
Period07-11-0207-11-05

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications

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  • Cite this

    He, K. Y., Chang, Y. S., & Lu, W-H. (2007). Improving identification of latent user goals through search-result snippet classification. In Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007 (pp. 683-686). [4427173] (Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007). https://doi.org/10.1109/WI.2007.4427173