A Hybrid Knowledge Discovery System Based on Items and Tags


  • Winyu Niranatlamphong College of Creative Design and Entertainment Technology, Dhurakij Pundit University
  • Worasit Choochaiwattana College of Creative Design and Entertainment Technology, Dhurakij Pundit University




Collaborative Filtering, Content-based Filtering, Item-Based Recommendation, Tag-Based Recommendation, Knowledge Recommender Service


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 tag-based 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.


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How to Cite

Niranatlamphong, W., & Choochaiwattana, W. (2009). A Hybrid Knowledge Discovery System Based on Items and Tags. Journal of Reviews on Global Economics, 6, 321–327. https://doi.org/10.6000/1929-7092.2017.06.32



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