Abstract:

Existing recommender systems do not take full advantage of personalization. To address this problem, a novel approach is proposed to mine the opinions and preference of users to build a personalized model for each user or item. Experimental results generated from a real data set show that the proposed approach can improve the accuracy of rating prediction.

Key words: personalized recommendation, recommender system, rating prediction, review comment

摘要：

针对现有基于评论分析的推荐算法没有充分考虑个性化的问题, 通过对评论进行主题分析, 挖掘用户的喜好, 分别建立基于用户和物品的个性化评分预测模型。在真实数据集上进行实验验证, 结果表明该模型有效地提高了推荐系统的评分预测性能。

关键词: 个性化推荐, 推荐系统, 评分预测, 评论信息