Incorporating user feedback into name disambiguation of scientific cooperation network
WAIM'11 Proceedings of the 12th international conference on Web-age information management
IdentityRank: Named entity disambiguation in the news domain
Expert Systems with Applications: An International Journal
Name disambiguation in scientific cooperation network by exploiting user feedback
Artificial Intelligence Review
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Due to homonyms, abbreviations, etc., name ambiguity is widely available in web and e-document. For example, when integrating heterogeneous literature databases, because there are different name specifications, different authors may be thought of as the same author, and vice versa. Therefore, name ambiguity makes data robust even dirty and lowers the precision of information retrieval. In this paper, we present an approach, named as Semantic Association based Name Disambiguation method (SAND), to solve person name ambiguity. The basic idea of SAND is to explore the semantic association of name entities and cluster name entities according to their associations. Finally, the name entities in the same group are considered as the same entities. We test SAND using data from CitesSeer, DBLP and Libra. The test results show that SAND is an effective approach to solve the problem of name ambiguity.