Classifying web queries by topic and user intent

Bernard J. Jansen, Danielle Booth

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

34 Scopus citations

Abstract

In this research, we investigate a methodology to classify automatically Web queries by topic and user intent. Taking a 20,000 plus Web query data set sectioned by topic, we manually classified each query using a three-level hierarchy of user intent. We note that significant differences in user intent across topics. Results show that user intent (informational, navigational, and transactional) varies by topic (15 to 24 percent depending on the category). We then use this manually classified data set to classify searches in a Web search engine query stream automatically, using an exact match followed by n-gram approach. These approaches have the advantage of being implementable in real time for query classification of Web searches. The implications are that a search engine can improve retrieval performance by more effectively identifying the intent underlying user queries.

Original languageEnglish (US)
Title of host publicationCHI 2010 - The 28th Annual CHI Conference on Human Factors in Computing Systems, Conference Proceedings and Extended Abstracts
Pages4285-4290
Number of pages6
DOIs
StatePublished - Jun 9 2010
Event28th Annual CHI Conference on Human Factors in Computing Systems, CHI 2010 - Atlanta, GA, United States
Duration: Apr 10 2010Apr 15 2010

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Other

Other28th Annual CHI Conference on Human Factors in Computing Systems, CHI 2010
CountryUnited States
CityAtlanta, GA
Period4/10/104/15/10

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

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  • Cite this

    Jansen, B. J., & Booth, D. (2010). Classifying web queries by topic and user intent. In CHI 2010 - The 28th Annual CHI Conference on Human Factors in Computing Systems, Conference Proceedings and Extended Abstracts (pp. 4285-4290). (Conference on Human Factors in Computing Systems - Proceedings). https://doi.org/10.1145/1753846.1754140