Case-based reasoning for identifying knowledge leader within online community
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摘要
Case-based Reasoning (CBR) has been extensively used as its capability to reuse previous solvable problems in recommending new solution through its adaptation strategy. In our work, CBR is chosen as the strategy to identify the leader of specific domain within the online community based on the profile that was developed through one's social participation and contribution as well as feedbacks from the community, called CBRIKL (CBR for Identifying Knowledge Leader). CBRIKL continuously builds leader profiles based on the identified knowledge domains and problems are assigned to them based on their expertise. The novelty introduced in the paper is on building a user profiling based on mixed sources in identifying leader and measuring and comparing strategy on expertise skill set in locating new knowledge leader. The methods and approaches that are developed are made to be usable to other problem domains
论文关键词:Case-based reasoning,Artificial intelligence,Expert profiling,Knowledge leader
论文评审过程:Received 19 February 2017, Revised 17 December 2017, Accepted 18 December 2017, Available online 18 December 2017, Version of Record 26 December 2017.
论文官网地址:https://doi.org/10.1016/j.eswa.2017.12.033