Community question answering sites provide us convenient and interactive platforms for problem solving and knowledge sharing, which are attracting an increasing number of users. Accordingly, it will be very common that different people have the same user name. When a query question is given, some potential answer providers would be recommended to the asker in the form of user name. However, some user names are ambiguous and not unique in the community. To help question askers match the ambiguous user names with the right people, in this paper, we propose to disambiguate same-name users by ranking their tag-based relevance to a query question. Empirical studies on three community question answering datasets demonstrate that our method is effective for disambiguating user names in community question answering.
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