A constraint-based topic modeling approach for
name disambiguation

doi:10.1007/s11704-009-0064-9

Front. Comput. Sci.

2010, Vol. 4

Issue (1) : 100-111 https://doi.org/10.1007/s11704-009-0064-9

Research articles

A constraint-based topic modeling approach for name disambiguation

Feng WANG,Jie TANG,Juanzi LI,Kehong WANG,

Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China;

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Abstract Name ambiguity refers to a problem that different people might be referenced with an identical name. This problem has become critical in many applications, particularly in online bibliography systems, such as DBLP and CiterSeer. Although much work has been conducted to address this problem, there still exist many challenges. In this paper, a general framework of constraint-based topic modeling is proposed, which can make use of user-defined constraints to enhance the performance of name disambiguation. A Gibbs sampling algorithm that integrates the constraints has been proposed to do the inference of the topic model. Experimental results on a real-world dataset show that significant improvements can be obtained by taking the proposed approach.

Keywords name disambiguation constraint topic model

Issue Date: 05 March 2010

Cite this article:

Feng WANG,Juanzi LI,Jie TANG, et al. A constraint-based topic modeling approach for name disambiguation[J]. Front. Comput. Sci., 2010, 4(1): 100-111.

URL:

https://academic.hep.com.cn/fcs/EN/10.1007/s11704-009-0064-9
https://academic.hep.com.cn/fcs/EN/Y2010/V4/I1/100

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