Expert Finding in Community Question Answering

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Miri Mohammad; Beigy hamid

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Seminar Paper

Paper Information

Seminar: INTERNATIONAL CONFERENCE ON WEB RESEARCH
Year:2020 | Issue:6

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Title

Expert Finding in Community Question Answering

Author(s)

Miri Mohammad | Beigy hamid

Keywords

Expert Finding

Community Question Answering

Word Embedding

StackOverflow

Abstract

Community Question Answering is a forum in which users ask their questions and other existing users respond those questions. As these forums grow, their users, questions and answers increase significantly and new challenges appear. For instance, someone who has asked a question in forum has to wait a lot to another user give him a response. On the other, experts has to spend a lot of time finding questions in their expertise field. Thus, the most important challenge which these forums face is finding appropriate users to answer the questions. One of the most critical issues which Expert Finding algorithms have is vocabulary gap between skills and words used in posts text. Therefore, in this paper, we propose two translation models to reduce vocabulary gap. The proposed models are evaluated using the StackOverflow dataset and compared with the related algorithms. The experimental results show the superiority of the proposed models.

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APA: Copy

Miri, Mohammad, & Beigy, hamid. (2020). Expert Finding in Community Question Answering. INTERNATIONAL CONFERENCE ON WEB RESEARCH. SID. https://sid.ir/paper/949262/en

Vancouver: Copy

Miri Mohammad, Beigy hamid. Expert Finding in Community Question Answering. 2020. Available from: https://sid.ir/paper/949262/en

IEEE: Copy

Mohammad Miri, and hamid Beigy, “Expert Finding in Community Question Answering,” presented at the INTERNATIONAL CONFERENCE ON WEB RESEARCH. 2020, [Online]. Available: https://sid.ir/paper/949262/en

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