关键词: 社会化标注系统, 个性化信息推荐, 推荐算法, 用户模型, 标签

Abstract: Many personalized resource recommendation methods based on social tagging ignore the different affects on recommendation of users’ long and short interests and polysemous tag for improving precision.In order to solve these problems，the metrics are designed for making a clear distinction between user’s long and short interests—— user’s tag preference weight and user’s resource preference weight.Based on the above，a novel hybrid recommend method has been proposed，which equilibrates both strength of content-based and collaborative filtering recommendation.The proposed method can eliminate influence of polysemous tag by adding the calculation factor of tagging the same resource tab vectors similarity.The experimental results show that this method for personalized resource recommendation in the social tagging system outperforms other recommendation algorithms.

Key words: social tagging system, personalized information recommendation, recommendation algorithm, user profile, tag