最后，分析了社会化标注中个性化信息推荐的研究，发现借助矩阵、聚类和网络的分析是三种主要思路。
Finally, studies on personalized information recommendation based on social tagging are analyzed, and find matrix, clustering and network analysis are three primarily methods.
本文在对社会化标注的内涵和结构加以简单介绍的基础上，重点探讨了基于社会化标注进行推荐的相关进展。
Based on the introduction of the meaning and structure of social tagging, this paper mainly discusses the advancements of personalized information recommendation based on social tagging.
为了改进当前社会化标注系统在标签浏览和检索方面的弱点，提出一种基于加权网络分割的社会性标签聚类算法。
This paper proposes a clustering algorithm of social tags based on weighed network division for the purpose of improving browsing and retrieval in existing social annotation system.
首先是明确了标签对于用户模型的意义，接着，从用户、资源和标签三个角度对基于社会化标注的聚类算法进行了讨论。
Firstly, tag 's meaning for user profile is proved, and clustering algorithms based on social tagging from the aspects of users, resources and tags are discussed.
首先是明确了标签对于用户模型的意义，接着，从用户、资源和标签三个角度对基于社会化标注的聚类算法进行了讨论。
Firstly, tag 's meaning for user profile is proved, and clustering algorithms based on social tagging from the aspects of users, resources and tags are discussed.
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