User authority ranking models for community question answering

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

1 Scopus Citations
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Author(s)

  • Yanghui Rao
  • Haoran Xie
  • Xuebo Liu
  • Fu Lee Wang
  • Tak-Lam Wong

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)2533-2542
Journal / PublicationJournal of Intelligent and Fuzzy Systems
Volume31
Issue number5
Publication statusPublished - 13 Oct 2016

Abstract

The proliferation of knowledge-sharing communities has generated large amounts of data. Prominent examples of how user-generated content can be harnessed include IBM's Watson question answering sytem and Apple's Siri, the question answering application in iPhones. Facing such massive data, user authority ranking is important to the development of question answering and other e-commerce services. In this study, we propose three probabilistic models to rank the user authority of each question. Compared to the existing approaches focused on the user relationship primarily, our method is more effective because we consider the link structure and topical similarities between users and questions simultaneously. We use a real-world dataset from Zhihu, a popular community question answering website in China to conduct experiments. Experimental results show that our model outperforms other baseline methods in ranking the user authority.

Research Area(s)

  • community question answering, topic modeling, User authority ranking

Citation Format(s)

User authority ranking models for community question answering. / Rao, Yanghui; Xie, Haoran; Liu, Xuebo et al.
In: Journal of Intelligent and Fuzzy Systems, Vol. 31, No. 5, 13.10.2016, p. 2533-2542.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review