摘要
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.
出处
《计算机科学与探索》
CSCD
2010年第3期240-246,共7页
Journal of Frontiers of Computer Science and Technology
基金
国家自然科学基金No.60773169
国家"十一五"科技支撑计划重大项目No.2006BAI05A01~~