基于信息熵的粗糙集页面推荐算法

Xiong Haijun, Zhang Qi, Wang Baoyi
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引用次数: 2

摘要

为了解决页面推荐的准确性和速度问题,我们利用正域数据的信息熵来帮助发现粗糙集规则。提出了一种新的基于信息熵的粗糙集重要属性挖掘算法,并在此基础上设计了网页推荐的启发式规则挖掘算法。最后利用推荐规则帮助网络用户找到自己感兴趣的页面。实验结果表明,该算法可以提高网页推荐的速度和准确性。
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Rough Set Page Recommendation Algorithm Based on Information Entropy
In order to solve the accuracy and speed problems of page recommendation, we used information entropy of data in positive domain to help finding out the rough set rules. A new rough set important attribute mining algorithm based on information entropy is put forward in this paper, according to which a heuristic rules mining algorithm of Web page recommendation is designed. At last we used the recommendation rules to help Web users to find out pages which are interested to them. The experiment results show that the algorithm can improve speed and accuracy of Web page recommendation.
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