Question routing via activity-weighted modularity-enhanced factorization
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Date
2022-12
Publication Type
Journal Article
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yes
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Abstract
Question Routing (QR) in Community-based Question Answering (CQA) websites aims at recommending newly posted questions to potential users who are most likely to provide “accepted answers”. Most of the existing approaches predict users’ expertise based on their past question answering behavior and the content of new questions. However, these approaches suffer from challenges in three aspects: (1) sparsity of users’ past records results in lack of personalized recommendation that at times does not match users’ interest or domain expertise, (2) modeling based on all questions and answers content makes periodic updates computationally expensive, and (3) while CQA sites are highly dynamic, they are mostly considered as static. This paper proposes a novel approach to QR that addresses the above challenges. It is based on dynamic modeling of users’ activity on topic communities. Experimental results on three real-world datasets demonstrate that the proposed model significantly outperforms competitive baseline models.
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published
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Journal / series
Volume
12
Pages / Article No.
155
Publisher
Springer
Event
Edition / version
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Software
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Date created
Subject
Question routing; Expert recommendation systems; Social network analysis; Community detection
Organisational unit
03784 - Helbing, Dirk / Helbing, Dirk
Notes
Funding
871042 - SoBigData++: An Integrated Infrastructures for Social Mining and Big Data Analytics (EC)