一种基于用户购买意向的个性化推荐模型

摘要

Along with the development of Internet technology,the rapid development of the field of O2O catering in-dustry developed rapidly.However,all the platforms are homogeneous and personalized recommendation system has become a main way to improve the users' experience and the profitability.While the traditional collaborative filtering could not rec-ommend accurately with the method of sparse data,this paper studies the effect of user's behavior on purchase intention in the context of O2O restaurant industry,taking the purchase behavior and the evaluation behavior into consideration.Then the user's interest and purchase intention is determined.Based on the model,the proposed method is compared with the traditional user-based collaborative filtering algorithm,which shows the efficiency of the proposed method.%伴随随着互联网技术的发展,O2O餐饮领域发展迅速,然而平台同质化严重,个性化推荐已经成为提升用户体验和提高运营水平的一种主要方式.而传统的协同过滤方法在数据稀疏的情况下,用户推荐准确率不高.本文研究基于O2O餐饮行业背景,研究用户的行为对购买意向的影响,综合考虑购买行为、评价行,为等多种用户行为,判断用户的兴趣点,从而确定用户的购买意向,提出一种基于多种用户行为的购买意向模型.基于此提出基于购买意向的推荐方法.最后通过与传统基于用户的协同过滤算法进行比较,确定了本文推荐方法的有效性.