计算机科学技术学报(英文版)
計算機科學技術學報(英文版)
계산궤과학기술학보(영문판)
COMPUTER JOURNAL OF SCIENCE AND TECHNOLOGY
2001年
2期
168-175
,共8页
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.
