Document (#26611)

Author
Huang, C.-K.
Chien, L.-F.
Oyang, Y.-J.
Title
Relevant term suggestion in interactive Web search based on contextual information in query session logs
Source
Journal of the American Society for Information Science and technology. 54(2003) no.7, S.638-649
Year
2003
Abstract
This paper proposes an effective term suggestion approach to interactive Web search. Conventional approaches to making term suggestions involve extracting co-occurring keyterms from highly ranked retrieved documents. Such approaches must deal with term extraction difficulties and interference from irrelevant documents, and, more importantly, have difficulty extracting terms that are conceptually related but do not frequently co-occur in documents. In this paper, we present a new, effective log-based approach to relevant term extraction and term suggestion. Using this approach, the relevant terms suggested for a user query are those that cooccur in similar query sessions from search engine logs, rather than in the retrieved documents. In addition, the suggested terms in each interactive search step can be organized according to its relevance to the entire query session, rather than to the most recent single query as in conventional approaches. The proposed approach was tested using a proxy server log containing about two million query transactions submitted to search engines in Taiwan. The obtained experimental results show that the proposed approach can provide organized and highly relevant terms, and can exploit the contextual information in a user's query session to make more effective suggestions.
Footnote
Teil eines Themenheftes: "Web retrieval and mining: A machine learning perspective"
Theme
Internet
Object
WWW

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  5. Li, X.; Schijvenaars, B.J.A.; Rijke, M.de: Investigating queries and search failures in academic search (2017) 0.37
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