A Bipartite Graph Based Social Network Splicing Method for Person Name Disambiguation

被引：0
|
作者：
Tang, Jintao [1 ,2 ]
Lu, Qin [1 ]
Wang, Ting [2 ]
Wang, Ji [3 ]
Li, Wenjie [1 ]
机构：
[1] Hong Kong Polytech Univ, Dept Comp, Hong Kong, Peoples R China
[2] Natl Univ Def Technol, Coll Comp, Changsha, Peoples R China
[3] Natl Lab Parallel & Distributed Proc, Changsha, Peoples R China
来源：
PROCEEDINGS OF THE 34TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL (SIGIR'11) | 2011年
关键词：
Person name disambiguation; Social network; Bipartite graph;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The key issue of person name disambiguation is to discover different namesakes in massive web documents rather than simply cluster documents by using textual features. In this paper, we describe a novel person name disambiguation method based on social networks to effectively identify namesakes. The social network snippets in each document are extracted. Then, the namesakes are identified via splicing the social networks of each namesake by using the snippets as a bipartite graph. Experimental results show that our method achieves better result than the top performance of WePS-2 in identifying different namesakes.
引用
收藏
页码：1233 / 1234
页数：2
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