A Hybrid Knowledge Discovery System Based on Items and Tags

Worasit Choochaiwattana () and Winyu Niranatlamphong
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Worasit Choochaiwattana: College of Creative Design and Entertainment Technology, Dhurakij Pundit University, Bangkok, Thailand

Journal of Reviews on Global Economics, 2017, vol. 6, 321-327

Abstract: Exponentially increasing knowledge in a management system is the main cause of the overload problem. Development of a recommender service embedded in the management system is challenging. This paper proposes a hybrid approach by combining an item-based recommendation technique (collaborative filtering technique) with a tagbased recommendation technique (content based filtering technique). In order to evaluate the performance of the proposed hybrid approach, a group of knowledge management system users are invited as participants in the research. Participants are asked to use the prototype of a management system embedded within the knowledge recommender service for four months, which guarantees that each interaction by participants with knowledge items are recorded. A confusion matrix is used to compute accuracy of the proposed hybrid approach. The results of the experiments reveal that the hybrid approach outperforms both item-based and tag-based approaches. The hybrid approach seems to be a promising technique for a recommender service in the knowledge management system.

Keywords: Collaborative Filtering; Content-based Filtering; Item-Based Recommendation; Tag-Based Recommendation; Knowledge Recommender Service. (search for similar items in EconPapers)
JEL-codes: D83 I23 O31 (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:lif:jrgelg:v:6:y:2017:p:321-327

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