建立一个基于用户偏好模型的标签推荐系统,从该系统产生的标签集合中选择出能降低一般性概念描述的模糊性的标签子集,推荐给用户。实验表明,该系统具有较高的可靠性和精准度。
Firstly,proposed a tag recommendation system based on user profile of preference.Then from the recommended tag set,selected some certain tags which could reduce the ambiguity of general concept description,and recommend could them to users finally.The experiments show that the final tags recommendation from the proposed system has better reliability and precision.