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Community discovery for knowledge collaborations in collective intelligence systems

Citation

Jiang, J and Bai, Q and Zhang, M, Community discovery for knowledge collaborations in collective intelligence systems, Journal of Information Processing, 22, (2) pp. 243-252. ISSN 1882-6652 (2014) [Refereed Article]

Copyright Statement

Copyright 2014 Information Processing Society of Japan

DOI: doi:10.2197/ipsjjip.22.243

Abstract

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.

Item Details

Item Type:Refereed Article
Keywords:community discovery, knowledge collaborative community, multi-domain problem solving, collective intelligence, community detection, collaborative intelligence
Research Division:Information and Computing Sciences
Research Group:Computer vision and multimedia computation
Research Field:Pattern recognition
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Application software packages
UTAS Author:Bai, Q (Dr Quan Bai)
ID Code:140668
Year Published:2014
Deposited By:Information and Communication Technology
Deposited On:2020-09-01
Last Modified:2020-10-23
Downloads:0

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