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このアイテムの引用には次の識別子を使用してください: http://hdl.handle.net/10119/4074

タイトル: Mining Query Logs for Improving Search Efficiency
著者: Tongchim, Shisanu
Sornlertlamvanich, Virach
Isahara, Hitoshi
キーワード: Query Clustering
Query Similarity
発行日: Nov-2007
出版者: JAIST Press
抄録: The understanding of how users use search queries is an important step towards developing successful web search engines. Mining search query log is a way to gain insight into user behavior. One technique used to analyze the query log is query clustering. Query clustering can be used to group semantically related queries, and can be used to gain an understanding of query usage. In this work, we focus on queries written in Thai language. A technique for query clustering is proposed. We first discuss the nature of Thai queries that makes this problem much more challenging. We examine the use of returned results from several search engines to enrich the meanings of queries. The experimental results show that query enrichment helps in finding the degree of similarity between any two queries. We apply a density-based clustering technique, called DBSCAN, for the query clustering task. Finally, we explore the use of clustered queries for query expansion.
記述: The original publication is available at JAIST Press http://www.jaist.ac.jp/library/jaist-press/index.html
KICSS 2007 : The Second International Conference on Knowledge, Information and Creativity Support Systems : PROCEEDINGS OF THE CONFERENCE, November 5-7, 2007, [Ishikawa High-Tech Conference Center, Nomi, Ishikawa, JAPAN]
言語: ENG
URI: http://hdl.handle.net/10119/4074
ISBN: 9784903092089
出現コレクション:KICSS 2007

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