多因素融合的个性化位置推荐算法

Personalized Location Recommendation Algorithm Mixing Multi-factors

位置推荐中影响推荐结果的主要因素有地理位置、个人爱好、社会关系以及时间周期,为有效融合4个影响因素并进行个性化位置推荐,针对每个因素构建对应的选择概率模型,并分析各因素对用户选择的影响力,在此基础上,提出一种启发式推荐算法。实验结果表明,与传统的基于位置的推荐算法相比,该算法性能更好,推荐的结果更能被用户所接受。

The main factors that influence the recommendation results in location recommendation system include location,personal interest,social relationship and time cycle.In order to effectively integrate 4 factors to personalized location recommendation,the corresponding selection probability model is constructed for each factor.The influence of 4 factors on user selection is analyzed.Finally,the heuristic recommendation algorithm is proposed by combining 4 factors.Experimental results show that,compared with the traditional location-based recommendation algorithm,the proposed algorithm has better performance and the recommended results are more acceptable to users.