Automatically discovering quality-assured consensual knowledge in social web

Although Social Web has been successful at encouraging vast numbers of contributors to collaboratively create and share knowledge, and leading to unanticipated explosion of innovative ideas, the user-generated contents are confronted with poor quality and untrustworthy problems, while the online community deals with several conflicts occurred during the deliberation. To tackle such problems, this paper presents a novel approach to enable an online community to achieve a potential position, a user-generated content that contains high quality and is acceptable by most members in the community. By structurally and semantically capturing and describing the community deliberation, a number of important properties of a potential position can be identified and used to propose several useful measures for automatically discovering quality-assured consensual knowledge in Social Web. The experimental results show that the proposed measures are efficient.

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