Recommender systems for personal knowledge management in collaborative environments

Authors:
Lu Zhen;Hai-Tao Song;Jun-Tao He
Affiliations:
School of Management, Shanghai University, 99 Shangda Road, Shanghai 200444, China;State Nuclear Power Engineering Corp. Ltd., Shanghai, China;School of Management, Shanghai University, 99 Shangda Road, Shanghai 200444, China
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

Citing 3
Cited 0

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Abstract

Personal knowledge management (PKM) is different from the traditional centralized knowledge management (KM) modes. The PKM is suitable for distributed collaborative KM environments. This paper makes an explorative study on the PKM, and analyzes various forms of personal knowledge resources in the product development process. Then a model of recommender systems for PKM is proposed for knowledge sharing among members in the collaborative environment. The key function of the PKM recommender systems is to supply potentially useful personal knowledge resources from the sites where these knowledge resources are created to the sites where the members may need the knowledge. The PKM is in a mode of distributed control rather than a mode of centralized control, which is widely used by traditional KM methods and tools. This study paves a way for developing an advanced mode of KM platforms for PKM sharing in collaborative environments.