fiee 15(2): e4

Research Article

Design of a Novel Intelligent Framework for Finding Experts and Learning Peers in Open Knowledge Communities

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  • @ARTICLE{10.4108/fiee.1.2.e4,
        author={Pengfei Wu and Shengquan Yu},
        title={Design of a Novel Intelligent Framework for Finding Experts and Learning Peers in Open Knowledge Communities},
        journal={EAI Endorsed Transactions on Future Intelligent Educational Environments},
        volume={1},
        number={2},
        publisher={ICST},
        journal_a={FIEE},
        year={2015},
        month={6},
        keywords={OKCs, right persons finding, SKN, ontology, linked data, SWRL, LDA, SNA, Learning Cell Knowledge Community},
        doi={10.4108/fiee.1.2.e4}
    }
    
  • Pengfei Wu
    Shengquan Yu
    Year: 2015
    Design of a Novel Intelligent Framework for Finding Experts and Learning Peers in Open Knowledge Communities
    FIEE
    ICST
    DOI: 10.4108/fiee.1.2.e4
Pengfei Wu1,2,3, Shengquan Yu1,2,*
  • 1: School of Educational Technology, Faculty of Education, Beijing Normal University, China
  • 2: The Joint Laboratory for Mobile Learning, Ministry of Education-China Mobile Communications Corporation, China
  • 3: Library, Shijiazhuang University, China
*Contact email: yusq@bnu.edu.cn

Abstract

Open knowledge communities (OKCs) are computer supported collaborative learning environments that provide opportunities for social knowledge construction, collaboration, participation and communication for ubiquitous learning and informal learning. However, with the rapid expanding of learning content resources and users, it is difficult for learners to find the right persons they need as knowledge experts and learning peers in OKCs using traditional search engines. To solve this problem, the paper presents a novel intelligent framework for finding the right experts and learning peers based on social knowledge network. After describing the architectural details of the framework, the authors elaborate on the intelligent framework design, the work principle, and mechanism of each module. Finally,the authors conclude by showing the learning application scenarios of this intelligent framework.