Abstract
Conventional Web search engines rank their searched results page by page. That is, conventionally, the information unit for both searching and ranking is a single Web page. There are, however, cases where a set of searched pages shows a better similarity (relevance) to a given (keyword) query than each individually searched page. This is because the information a user wishes to have is sometimes distributed on multiple Web pages. In such cases, the information unit used for ranking should be a set of pages rather than a single page. In this paper, we propose the notion of a “page set ranking”, which is to rank each pertinent set of searched Web pages. We describe our new algorithm of the page set ranking to efficiently construct and rank page sets. We present some experimental results and the effectiveness of our approach.
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Yumoto, T., Tanaka, K. (2006). Page Sets as Web Search Answers. In: Sugimoto, S., Hunter, J., Rauber, A., Morishima, A. (eds) Digital Libraries: Achievements, Challenges and Opportunities. ICADL 2006. Lecture Notes in Computer Science, vol 4312. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11931584_27
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DOI: https://doi.org/10.1007/11931584_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-49375-4
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