Abstract
The conventional Web search has two problems. The first is that users’ search intentions are diverse. The second is that search engines return a huge number of search results which are not ordered correctly. These problems decrease the accuracy of Web searches. To solve these problems, in our past work, we proposed a reranking system based on the user’s search intentions whereby the user edits a part of the search results and the editing operations are propagated to all of the results to rerank them. In this paper, we propose methods of reranking Web search results that depend on the user’s delete and emphasis operations. Then, we describe their evaluation. In addition, we propose a method to support deletion and emphasis by using Tag-Clouds.
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
Yamamoto, T., Nakamura, S., Tanaka, K.: An Editable Browser for Reranking Web Search Results. In: Proceedings of the Third International Special Workshop on Databases for Next-Generation Researchers (2007)
Broder, A.: A taxonomy of web search. ACM SIGIR Forum 36(2), 3–10 (2002)
Morphological analyzer: ChaSen. http://chasen.naist.jp/hiki/ChaSen/
flickr. http://www.flickr.com/
Kang, I.H., Kim, G.C.: Query type classification for web document retrieval. In: Proceedings of SIGIR 2006, pp. 64–71 (2006)
Lee, U., Liu, Z., Cho, J.: Automatic identification of user goals in Web search. In: Proceedings of WWW 2005, pp. 391–400 (2005)
Onoda, T., Murata, H., Yamada, S.: Non-Relevance Feedback Document Retrieval Based on One Class SVM and SVDD. In: 2006 IEEE World Congress on Computational Intelligence, pp. 2191–2198 (2006)
Rose, D.E., Levinson, D.: Understanding user goals in web search. In: Proceedings of the WWW 2004, pp. 13–19 (2004)
Salton, G.: The SMART Retrieval System Experiments in Automatic Document Processing. pp. 312–323 (1971)
Salton, G., McGill, M.J.: Introduction to Modern Information Retrieval. McGraw-Hill, New York (1986)
Yahoo! Mindset. http://mindset.research.yahoo.com/
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yamamoto, T., Nakamura, S., Tanaka, K. (2007). Rerank-by-Example: Efficient Browsing of Web Search Results. In: Wagner, R., Revell, N., Pernul, G. (eds) Database and Expert Systems Applications. DEXA 2007. Lecture Notes in Computer Science, vol 4653. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74469-6_78
Download citation
DOI: https://doi.org/10.1007/978-3-540-74469-6_78
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74467-2
Online ISBN: 978-3-540-74469-6
eBook Packages: Computer ScienceComputer Science (R0)