Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/39861
Title: A bipartite graph based social network splicing method for person name disambiguation
Authors: Tang, J
Lu, Q 
Wang, T
Wang, JI
Li, W 
Keywords: Bipartite graph
Person name disambiguation
Social network
Issue Date: 2011
Source: SIGIR '11 Proceedings of the 34th international ACM SIGIR Conference on Research and Development in Information Retrieval , Beijing, China, July 24-28, 2011, p. 1233-1234 How to cite?
Abstract: 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.
URI: http://hdl.handle.net/10397/39861
ISBN: 978-1-4503-0757-4
DOI: 10.1145/2009916.2010135
Appears in Collections:Conference Paper

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