基于TF-IDF相似度的标签聚类方法

TF-IDF Similarity Based Method for Tag Clustering

社会标签系统是Web2.0中提出的新概念,旨在更好地表达用户的兴趣和意愿。标签聚类是社会标签数据挖掘中一个非常重要的研究课题。标签相似度的计算是标签聚类的关键技术。主要工作包括:(1)提出了一种基于TF-IDF的标签相似度计算方法和基于该相似度的聚类算法;(2)分析了影响标签相似度的条件;(3)通过实验表明:与已有方法相比,新方法的准确性更高。

As a new concept of Web 2.0, social tagging system aims at expressing users＇ interests clearly and specifically. Tag clustering is an important research topic in social tagging system mining. Evaluation similarity a mong social tags is the key technique in tag clustering. The main contributions include ： （ 1 ） introduce a new method to calculate the tag similarity based on TF-IDF, and propose a clustering algorithm based on the new method; （2） analyze the conditions that influence tag similarity; （3） conduct extensive experiments to demonstrate that proposed method is more efficient compared with some methods proposed before.