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- W337820460 abstract "Disambiguating person names in a set of documents (e.g. research papers or Web pages) is a critical problem in many knowledge management applications. The phenomenon of ambiguity will deteriorate the quality of service, such as the scholar searching and expert finding. Despite years of research, this problem remains largely unsolved, where the unknown number of persons with the same name and the information scarcity in documents pose many difficulties and challenges. In this paper, we formalize name disambiguation as a collective classification problem and solve it using a simple yet effective iterative classification algorithm, referred as ICAND (i.e. Iterative Classification Algorithm for Name Disambiguation). Experimental results on researcher dataset show that the proposed approach can significantly outperform several baseline methods." @default.
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- W337820460 date "2014-01-01" @default.
- W337820460 modified "2023-09-27" @default.
- W337820460 title "Name Disambiguation by Collective Classification" @default.
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- W337820460 doi "https://doi.org/10.1007/978-3-319-12844-3_35" @default.
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