Topic sensitive hybrid expertise retrieval system in community question answering services
作者：
Highlights：
• Defines and uses three expertise signatures from a topic sensitive perspective: knowledge, reputation, and authority.
• The knowledge considers previously answered questions with distributions of topics similar to the new question.
• The reputation makes use of the qualities of previously answered questions with similar distributions of topics.
• The authority model takes into account questions and the relationships among their answerers.
摘要
•Defines and uses three expertise signatures from a topic sensitive perspective: knowledge, reputation, and authority.•The knowledge considers previously answered questions with distributions of topics similar to the new question.•The reputation makes use of the qualities of previously answered questions with similar distributions of topics.•The authority model takes into account questions and the relationships among their answerers.
论文关键词：Community question answering,Expertise retrieval,Social network analysis,Topic sensitive model
论文评审过程：Received 2 November 2019, Revised 27 July 2020, Accepted 13 October 2020, Available online 14 October 2020, Version of Record 20 October 2020.
论文官网地址：https://doi.org/10.1016/j.knosys.2020.106535
