CAJ | 학술논문

通过分析电子商务网站的 Web 服务器日志提取网络消费者的商品浏览行为信息,利用消费者的浏览频率、浏览时间、链接路径数及路径深度估计商品对网络消费者当前浏览期间偏好的影响权重.结合双向关联规则理论和 Apriori 算法挖掘具有相互依赖关系的商品,找出网络消费者的商品偏好浏览路径,根据消费者当前的浏览行为发现其可能感兴趣的商品,并进一步计算消费者对商品的偏好程度.最后利用自主开发的旅游电子商务网站的Web 日志数据进行仿真实验,挖掘网络消费者的旅游偏好.实验结果表明,在相同的实验条件下,与基于关联规则的偏好挖掘方法相比,基于双向关联规则的偏好挖掘方法的推荐精度增加,推荐覆盖率扩大.
통과분석전자상무망참적 Web 복무기일지제취망락소비자적상품류람행위신식,이용소비자적류람빈솔、류람시간、련접로경수급로경심도고계상품대망락소비자당전류람기간편호적영향권중.결합쌍향관련규칙이론화 Apriori 산법알굴구유상호의뢰관계적상품,조출망락소비자적상품편호류람로경,근거소비자당전적류람행위발현기가능감흥취적상품,병진일보계산소비자대상품적편호정도.최후이용자주개발적여유전자상무망참적Web 일지수거진행방진실험,알굴망락소비자적여유편호.실험결과표명,재상동적실험조건하,여기우관련규칙적편호알굴방법상비,기우쌍향관련규칙적편호알굴방법적추천정도증가,추천복개솔확대.
@@@@By analysis of web server logs in e - commerce to extract the information of web consumer ’s products browsing behavior ,the weight of a product of web consumer’s current preference has been estimated by means of consumer’s browsing frequency ,browsing time ,the number of paths and links depth .The theory of bidirectional association rules was combined with the idea of Apriori to find out interdependent products with to discover consumer’s product preference path ,candidate products of consumer preferred have been found based on consumer’ s current browsing behavior ,and then each preference degree of consumer to those products has been calculated respectively .Finally ,the web server logs of a self - developed e - commerce web site has been used in the simulation to find out web consumers tour preference . Experimental results shows that the recommendation accuracy of preference mining method based on bidirectional association rules has improved greatly and the coverage has been expanded compared with preference mining method based on association rules when the experimental condition is equal .