摘要
个性化推荐技术在电子商务系统中得到了广泛应用.但现有的个性化推荐模型不能反映出商品的某些特殊属性对用户购买行为的影响及用户购买某商品的真正原因.引入生物界中基因的概念,提出了基于商品基因的个性化推荐模型,发现用户钟爱商品基因,并将钟爱商品基因遗传到用户选择的商品.该模型能更好地发现用户的购买动机,从而进一步提高个性化推荐精度和用户满意度.
the current Personalized recommendation technology has been widely applied in e -commerce. However, personalized recommendation models do not consider the influence of items＇ special attributes on user purchasing behavior, and the real reasons that users buy one item. After introducing the concept of gene used in biology, a model based on item gene is proposed, which found item gene preferred by users and inherited them to the chosen items. The model can identified users＇ purchasing motivation better, so it can improve the recommendation accuracy and customer satisfaction.
出处
《辽宁大学学报（自然科学版）》
CAS
2009年第4期329-334,共6页
Journal of Liaoning University：Natural Sciences Edition
关键词
电子商务
个性化推荐
推荐模型
商品基因
推荐精度
E - commerce
personalized recommendation
recommendation model
item gene
recommendation accuracy.
作者简介
作者简介：夏秀峰（1964-），男，山东胶南人，博士，教授，从事数据库理论与技术研究
