中文摘要：

个性化推荐对于提升网络购物的效率、促进产品的销售具有非常重要的影响，如何提升个性化推荐的效果受到了研究人员的广泛关注。先前研究大多数关注如何提升推荐算法的精确性和效率，或者关注如何提升消费者的推荐满意度以及个性化推荐采纳的影响因素。与既往研究不同，本文首先阐述了目前推荐系统采用的主流算法，而后基于管理和消费者行为的视角，从推荐时机、推荐产品组合、推荐效果三方面重点介绍了目前以该视角对个性化推荐的研究现状及研究成果，指出该研究方向具有较大的挖掘空间和研究价值，最后提出个性化推荐未来的研究趋势与展望。

英文摘要：

Personalized recommendation has great influence on raising online shopping efficiency and increasingproduct sales. The ways to provide more efficient personalized recommendations have drawn researchers＇ atten-tion. Most existing studies focus on how to improve the accuracy and efficiency of the recommendation algo-rithms, or are more concerned about ways to increase consumer satisfaction and the impact factors of personalizedrecommendation adoption. Unlike previous studies, first the current mainstream algorithms of recommendationsystem are summarized. Then based on the perspectives of management and consumer behavior, the current re-search status and results of personalized recommendation are mainly introduced from three aspects ： recommenda-tion timing, recommendation product portfolio and recommendation efficiency. It is pointed out the research ofpersonalized recommendation has much potential and research value, and finally the future research trends andprospects are put forward.