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- W2012076061 abstract "In this information-explosion era, the quality of collective intelligence is not easy to control. Knowledge demanders are required to invest an amount of time in evaluating the collective intelligence quality of virtual community to acquire correct knowledge. In addition, some knowledge providers might provide poor quality information in this circumstance and overall collective intelligence quality would be affected. The knowledge providers would reduce the willingness to share knowledge. Therefore, this paper develops a virtual community question and answer suitability determination (QASD) model to enhance collective intelligence quality. This proposed model analyzes the Q&A title, Q&A content, and the discussion and employs keyword extraction, article’s core information extraction, article similarity determination and semantic analysis techniques to determine the quality of Q&A, the suitability of Q&A content, and the suitability of Q&A semantics. After that, the integrated suitability score between tar..." @default.
- W2012076061 created "2016-06-24" @default.
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- W2012076061 date "2014-08-18" @default.
- W2012076061 modified "2023-09-24" @default.
- W2012076061 title "A virtual community question and answer suitability determination model" @default.
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- W2012076061 doi "https://doi.org/10.1080/21681015.2014.966870" @default.
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