Predicting DataSpace Retrieval Using Probabilistic Hidden Information
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概要
- 論文の詳細を見る
This paper discusses the issues involved in the design of a complete information retrieval system for DataSpace based on user relevance probabilistic schemes. First, Information Hidden Model (IHM) is constructed taking into account the users perception of similarity between documents. The system accumulates feedback from the users and employs it to construct user oriented clusters. IHM allows integrating uncertainty over multiple, interdependent classifications and collectively determines the most likely global assignment. Second, Three different learning strategies are proposed, namely query-related UHH, UHB and UHS (User Hidden Habit, User Hidden Background, and User Hidden keyword Semantics) to closely represent the user mind. Finally, the probability ranking principle shows that optimum retrieval quality can be achieved under certain assumptions. An optimization algorithm to improve the effectiveness of the probabilistic process is developed. We first predict the data sources where the query results could be found. Therefor, compared with existing approaches, our precision of retrieval is better and do not depend on the size and the DataSpace heterogeneity.
- （社）電子情報通信学会の論文
- 2010-07-01
著者
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LIU Shuoyan
Institute of Computer Science and Engineering, Beijing Jiaotong University
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XU De
Institute of Computer Science and Engineering, Beijing Jiaotong University
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WANG Ning
Institute of Computer Science and Engineering, Beijing Jiaotong University
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Xu De
Institute Of Computer & Engineering Beijing Jiaotong University
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Wang Ning
Institute Of Computer And Engineering Beijing Jiaotong University
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Xu De
Institute Of Computer And Engineering Beijing Jiaotong University
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FANZOU TCHUISSANG
Institute of Computer and Engineering, Beijing Jiaotong University
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KUICHEU Nathalie
Institute of Computer and Engineering, Beijing Jiaotong University
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SIEWE Francois
Software Technology Research Laboratory, Faculty of Technology, De Montfort University
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Kuicheu Nathalie
Institute Of Computer And Engineering Beijing Jiaotong University
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Siewe Francois
Software Technology Research Laboratory Faculty Of Technology De Montfort University
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Fanzou Tchuissang
Institute Of Computer And Engineering Beijing Jiaotong University
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Liu Shuoyan
Institute Of Computer And Engineering Beijing Jiaotong University
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Liu Shuoyan
Institute Of Computer & Engineering Beijing Jiaotong University
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