Abstract
We report on a study that was undertaken to better identify users’ goals behind web search queries by using click through data. Based on user logs which contain over 80 million queries and corresponding click through data, we found that query type identification benefits from click through data analysis; while anchor text information may not be so useful because it is only accessible for a small part (about 16%) of practical user queries. We also proposed two novel features extracted from click through data and a decision tree based classification algorithm for identifying user queries. Our experimental evaluation shows that this algorithm can correctly identify the goals for about 80% web search queries.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Broder, A.: A taxonomy of web search. SIGIR Forum 36(2), 3–10 (2002)
Rose, D.E., Levinson, D.: Understanding User Goals in Web Search. In: Proceedings of the 13th World-Wide Web Conference (2004)
Craswell, N., Hawking, D.: Overview of the TREC-2002 web track. In: The eleventh Text Retrieval Conference (TREC-2002), NIST (2003)
Craswell, N., Hawking, D.: Overview of the TREC-2003 web track. In: The twelfth Text REtrieval Conference (TREC 2003), NIST (2004)
Craswell, N., Hawking, D., Robertson, S.: Effective Site Finding using Link Anchor Information. In: Proceedings of ACM SIGIR 2001 (2001)
Kraaij, W., Westerveld, T., Hiemstra, D.: The importance of prior probabilities for entry page search. In: Proceedings of ACM SIGIR 2002 (2002)
Bharat, K., Henzinger, M.: Improved algorithms for topic distillation in a hyperlinked environment. In: Proceedings of ACM SIGIR 1998 (1998)
Lee, U., Liu, Z., Cho, J.: Automatic Identification of User Goals in Web Search. In: Proceedings of the 14th World-Wide Web Conference (2005)
Kang, I., Kim, G.: Query type classication for web document retrieval. In: Proceedings of ACM SIGIR 2003 (2003)
Craswell, N., Hawking, D.: Overview of the TREC-2004 Web track. In: The Thirteenth Text REtrieval Conference Proceedings (TREC 2004), NIST (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Liu, Y., Zhang, M., Ru, L., Ma, S. (2006). Automatic Query Type Identification Based on Click Through Information. In: Ng, H.T., Leong, MK., Kan, MY., Ji, D. (eds) Information Retrieval Technology. AIRS 2006. Lecture Notes in Computer Science, vol 4182. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11880592_51
Download citation
DOI: https://doi.org/10.1007/11880592_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45780-0
Online ISBN: 978-3-540-46237-8
eBook Packages: Computer ScienceComputer Science (R0)