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- W1996203480 abstract "Expert finding in bibliographic networks has received increased interests in recent years. This task concerns with finding relevant researchers for a given topic. Motivated by the observation that rarely do all coauthors contribute to a paper equally, in this paper, we propose a discriminative method to realize leading authors contributing in a scientific publication. Specifically, we cast the problem of expert finding in a bibliographic network to find leading experts in a research group, which is easier to solve. According to some observations, we recognize three feature groups that can discriminate relevant and irrelevant experts. Experimental results on a real dataset, and an automatically generated one that is gathered from Microsoft academic search show that the proposed model significantly improves the performance of expert finding in terms of all common Information Retrieval evaluation metrics." @default.
- W1996203480 created "2016-06-24" @default.
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- W1996203480 date "2013-01-01" @default.
- W1996203480 modified "2023-09-24" @default.
- W1996203480 title "Expertise retrieval in bibliographic network" @default.
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- W1996203480 doi "https://doi.org/10.1145/2505515.2505697" @default.
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