GHOST: an effective graph-based framework for name distinction

Authors:
Xiaoming Fan;Jianyong Wang;Bing Lv;Lizhu Zhou;Wei Hu
Affiliations:
Tsinghua University, Beijing, China;Tsinghua University, Beijing, China;Tsinghua University, Beijing, China;Tsinghua University, Beijing, China;Tsinghua University, Beijing, China
Venue:
Proceedings of the 17th ACM conference on Information and knowledge management
Year:
2008

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Abstract

Name ambiguity stems from the fact that many people or objects share identical names. In this paper, we focus on investigating the problem in digital libraries to distinguish publications written by authors with identical names. We present an effective graph-based framework, GHOST (abbr. GrapH-based framewOrk for name diStincTion), to solve the problem systematically. We evaluated the framework on the real DBLP dataset, and the experimental results show that GHOST outperforms the state-of-the-art method.