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《Journal of Anshan University of Science and Technology》 2004-06
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Network services of personalized recommendation based on association rules

LIAO Ya-li, WANG Xi-gang, ZHAN Xue-gang (School of Computer Science and Engineering,Anshan University of Science and Technology,Anshan 114044,China)  
Mining useful association rules from volumes of customers' on-line purchasing histories is an important technology for efficient personalized service.By analyzing and mining the customers' on-line purchasing on an internet bookshop,the association rules was find by means of Apriori algorithm.Then the patterns for frequently purchasing were extracted by filtering support degrees.The candidating webs to be recommendated can be determined according to the customers' interest degree and the credibility of the rules,so that personalization recommendation services could be provided.
【CateGory Index】: TP393
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