计算机科学与探索2012，Vol.6Issue(8)：717-725,9.DOI:10.3778/j.issn.1673-9418.2012.08.005
在线百科间的标签推荐算法
Tag Recommendation among Different Online Encyclopedia Systems
摘要
Abstract
Online encyclopedia systems have become an important way for people to acquire knowledge. As an important part of online encyclopedia systems, tags of each page not only help users get more relevant information for further reading, but also enhance the efficiency of the retrieval system. After taking full advantage of linkage relations between pages of online encyclopedia systems, this paper proposes a new method, HVSM (homogeneous principle based vector space model), which is universal and aims at recommending tags between different online encyclopedia systems. Experimental results show that this method can achieve a good accuracy which is higher than NAM (naive recommendation model). Some useful conclusions are obtained through the analysis of experimental results, which lay a solid foundation for further research.关键词
在线百科系统/标签推荐/同质性原理/向量空间模型Key words
online encyclopedia system/ tag recommendation/ homogeneous principle/ vector space model分类
信息技术与安全科学引用本文复制引用
刘阔,姚舒扬,邓志鸿..在线百科间的标签推荐算法[J].计算机科学与探索,2012,6(8):717-725,9.基金项目
The National Natural Science Foundation of China under Grant No.61170091(国家自然科学基金) （国家自然科学基金）
the National High-Tech Research and Development Plan of China under Grant No.2009AA01Z136(国家高技术研究发展计划(863)). （国家高技术研究发展计划(863）
