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题名:
query model refinement using word graphs
作者: Huang Yunping ; Sun Le ; Nie Jian-Yun
会议文集: International Conference on Information and Knowledge Management, Proceedings
会议名称: 19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10
会议日期: 40842
出版日期: 2010
会议地点: Toronto, ON, Canada
关键词: Image retrieval ; Knowledge management ; Query processing ; Random processes
出版地: United States
收录类别: EI
ISBN: 9781450000000
部门归属: (1) Institute of Software, Chinese Academy of Sciences, Beijing, China; (2) Department of Computer Science and Operations Research, University of Montreal, Canada
主办者: ACM SIGIR; ACM SIGWEB; ACM SIGKDD
英文摘要: Pseudo relevance feedback method is an effective method for query model refinement. Most existing pseudo relevance feedback methods only take into consideration the term distribution of the feedback documents, but omit the term's context information. This paper presents a graph-based method to improve query models, in which a word graph is constructed to encode terms and their co-occurrence dependencies within the feedback documents. Using a random walk, the weight of each term in the graph can be determined in a context-dependent manner, i.e. the weight of a term is strongly dependent on the weights of the connected context terms. Our experimental results on four TREC collections show that our proposed approach is more effective than the existing state-of-the-art approaches. © 2010 ACM.
内容类型: 会议论文
URI标识: http://ir.iscas.ac.cn/handle/311060/8874
Appears in Collections:基础软件国家工程研究中心_会议论文

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Recommended Citation:
Huang Yunping,Sun Le,Nie Jian-Yun. query model refinement using word graphs[C]. 见:19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10. Toronto, ON, Canada. 40842.
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