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- CHEN Fei
CHEN Fei
Tsinghua National Laboratory for Information Science and Technology(Tsinghua University), Beijing 100084, China;Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
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Search for this author on this site - LIU Yi-Qun
LIU Yi-Qun
Tsinghua National Laboratory for Information Science and Technology(Tsinghua University), Beijing 100084, China;Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
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Search for this author on this site - ZHANG Min
ZHANG Min
Tsinghua National Laboratory for Information Science and Technology(Tsinghua University), Beijing 100084, China;Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
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Search for this author on this site - MA Shao-Ping
MA Shao-Ping
Tsinghua National Laboratory for Information Science and Technology(Tsinghua University), Beijing 100084, China;Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
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National Natural Science Foundation of China (61532011, 61472206); National Program on Key Basic Research Project of China (973 Program) (2015CB358700)
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To evaluate search result diversification, which is supposed to meet different needs behind a same query, a number of evaluation frameworks are proposed. Although most of these frameworks take the probability distribution of information needs(usually called subtopics) underlying a query topic into account, they usually do not consider the subtopic taxonomy information. In this paper, the decay function is first introduced to take the subtopic taxonomy information into account. And then based on the decay function, a novel framework called the subtopic taxonomy-aware(STA) framework is proposed to define the structure that the taxonomy-aware diversity evaluation metrics would have. The decay functions used for the informational and navigational subtopics are also discussed. Experiments based on TREC and NTCIR test collections show the effectiveness of the proposed method.
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陈飞,刘奕群,张敏,马少平.基于查询子主题分类的多样性搜索评价方法.软件学报,2015,26(12):3130-3139
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History
- Received:December 13,2013
- Revised:September 26,2014
- Online: December 04,2015
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-4
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