Abstract
In this paper, keyword map-based relevance feedback is applied to interactive Blog search.There exists vast amount of information in the Web, from which users usually gather information without definite information needs. In particular, when exploring the Blog space, the range of user’s interests is expected to be broader than usual Web browsing process. The relevance feedback techniques have been studied in the field of document retrieval, aiming to generate appropriate queries for users’ information needs.Although this approach is effective when the assumption that a user has a concrete criteria on the relevance of retrieved documents holds, it could not always hold when searching Blog, which consists of vast number of short articles about various topics. Compared with the previous work on keyword map-based relevance feedback, the algorithm proposed in this paper can consider multiple topics, in which a user is interested on the keyword map.
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© 2005 Springer-Verlag Berlin Heidelberg
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Takama, Y., Kajinami, T., Matsumura, A. (2005). Blog Search with Keyword Map-Based Relevance Feedback. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3614. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11540007_160
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DOI: https://doi.org/10.1007/11540007_160
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28331-7
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