Abstract
This paper proposes a method to allow users to search for Web pages according to their search intentions. We introduce a degree of “unconfidence” for each term in a Web search query. We first investigate the relationships among query terms by accessing a Web search engine. Next, according to a degree of users’ unconfidences for each query term and the relationships among query terms, our system finds alternative terms by accessing to a Web search engine. Then, our system generates a collection of new queries that are different from the original query and merges the Web search results obtained for each new query. We implemented our system and showed the usefulness of our system based on user evaluation.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Ohshima, H., Oyama, S., Tanaka, K.: Searching Coordinate Terms with Their Context from the Web. In: Proc. of WISE 2007, pp. 40–47 (2007)
Shinzato, K., Torisawa, K.: A Simple WWW-based Method for Semantic Word Class Acquisition. In: Proc. of the Recent Advances in Natural Language Processing, pp. 493–500 (2005)
Ghahramani, Z., Heller, K.: Bayesian sets. Advances in Neural Information Processing Systems 18 (2005)
White, R.W., Morris, D.: Investigating the querying and browsing behavior of advanced search engine users. In: Proc. of SIGIR 2007, pp. 255–262 (2007)
Noda, T., Ohshima, H., Tezuka, T., Tanaka, K.: Web information retrieval by extraction of topic terms from subject terms. DBSJ Letters 5(2), 65–68 (2006)
Kang, I.-H., Kim, G.: Query type classification for web document retrieval. In: Proc. of SIGIR 2003, pp. 64–71 (2003)
Lee, U., Liu, Z., Cho, J.: Automatic identification of user goals in web search. In: Proc. of the 14th international conference on World Wide Web, pp. 391–400 (2005)
Rocchio, J.: Relevance feedback in information retrieval. The SMART Retrieval System: Experiments in Automatic Document Processing, 313–323 (1971)
Tan, B., Velivelli, A., Fang, H., Zhai, C.: Term Feedback for Information Retrieval with Language Models. In: Proc. of SIGIR 2007, pp. 263–270 (2007)
Jones, R., Rey, B., Madani, O., Greiner, W.: Generating query substitutions. In: Proc. of the 15th international conference on World Wide Web, pp. 387–396 (2006)
Kraft, R., Zien, J.: Mining anchor text for query refinement. In: Proc. of the 13th international conference on World Wide Web, pp. 666–674 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kaneko, Y., Nakamura, S., Ohshima, H., Tanaka, K. (2008). Query Relaxation Based on Users’ Unconfidences on Query Terms and Web Knowledge Extraction. In: Buchanan, G., Masoodian, M., Cunningham, S.J. (eds) Digital Libraries: Universal and Ubiquitous Access to Information. ICADL 2008. Lecture Notes in Computer Science, vol 5362. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89533-6_8
Download citation
DOI: https://doi.org/10.1007/978-3-540-89533-6_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89532-9
Online ISBN: 978-3-540-89533-6
eBook Packages: Computer ScienceComputer Science (R0)