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Community discovery for knowledge collaborations in collective intelligence systems
Knowledge collaborative communities play an important role in collective intelligence systems. To discover a knowledge collaborative community, we need to consider not only the structure of a network but also the performance of knowledge collaboration among members within the community. Traditional community discovery approaches are not suitable to discover knowledge collaborative communities since most of them focus too much on the network topologies, and ignore some other important factors. In this paper, we propose two community discovery approaches, which can be used in different sizes of networks, and take more knowledge collaboration factors into account. Compared with some other existing approaches, the proposed approach can perform better in forming knowledge collaborative communities for multi-domain problem solving.
History
Publication title
Journal of Information ProcessingVolume
22Pagination
243-252ISSN
1882-6652Department/School
School of Information and Communication TechnologyPublisher
Information Processing Society of JapanPlace of publication
JapanRights statement
Copyright 2014 Information Processing Society of JapanRepository Status
- Restricted