Evolving information filtering for personalized information service |
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Authors: | Fanjiang Tian Congrong Li Dingxing Wang |
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Affiliation: | (1) Department of Computer Science and Technology, Tsinghua University, 100084 Beijing, P.R. China |
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Abstract: | Information filtering (IF) systems are important for personalized information service. However, most current IF systems suffer from low quality and long training time. In this paper, a refined evolving information filtering method is presented. This method describes user's information need from multi-aspects and improves filtering quality through a process like natural selection. Experimental result shows this method can shorten training time, improve filtering quality, and reduce the relevance between filtering results and training sequence. |
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Keywords: | information filtering information processing personalized information service |
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