Bernard J. Jansen
Danielle Booth
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.
- Beitzel, S. M., Jensen, E. C., Chowdhury, A. and Frieder, O. Varying approaches to topical web query classification. In Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval (Amsterdam, The Netherlands, 23 -- 27 July, 2007), 783 -- 784. Google Scholar
Digital Library
- Beitzel, S. M., Jensen, E. C., Lewis, D. D., Chowdhury, A. and Frieder, O. Automatic classification of Web queries using very large unlabeled query logs ACM Transactions on Information Systems, 25, 2 (2007), Article No. 9. Google ScholarDigital Library
- Broder, A. A Taxonomy of Web Search. SIGIR Forum, 36, 2 (2002), 3--10. Google ScholarDigital Library
- Jansen, B. J., Booth, D. and Spink, A. Determining the informational, navigational, and transactional intent of Web queries. Information Processing & Management, 44, 3 (2008), 1251--1266. Google ScholarDigital Library
- Pirolli, P. Information Foraging Theory: Adaptive Interaction with Information. Oxford University Press, Oxford, 2007. Google ScholarDigital Library
- Rose, D. E. and Levinson, D. Understanding User Goals in Web Search. In Proceedings of the World Wide Web Conference (WWW 2004) (New York, NY, USA, 17--22 May, 2004), 13--19. Google ScholarDigital Library
- Shen, D., Pan, R., Sun, J.-T., Pan, J. J., Wu, K., Yin, J. and Yang, Q. Query enrichment for web-query classification Transactions on Information Systems, 24, 3 (2006), 320 -- 352. Google ScholarDigital Library
Index Terms
- Classifying web queries by topic and user intent
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