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 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.
Highlights
With the advancement of information technology, modern businesses exploit the usage of various information systems to improve their daily productivity and to gain competitive advantages over their competitors
When a tremendous collection of knowledge is stored in the knowledge management system, its users will encounter the problem of knowledge overload
This paper investigated how well a combination of collaborative filtering, called item-based recommendation, and content-based filtering, called tag-based recommendation, augments the task of automated knowledge dissemination services in a knowledge management system
Summary
With the advancement of information technology, modern businesses exploit the usage of various information systems to improve their daily productivity and to gain competitive advantages over their competitors. Information and knowledge become the most important critical factors for the success of modern businesses. A knowledge management system helps the employees of a business organization to store, retrieve and disseminate their knowledge, and allows the business organization to maintain its core knowledge. When a tremendous collection of knowledge is stored in the knowledge management system, its users will encounter the problem of knowledge overload. One way to overcome the problem of knowledge overload is to develop an automatic knowledge dissemination mechanism, or a knowledge recommender service. The experimental setting and evaluation are explained in a proposed hybrid mechanism.
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