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Recommender systems for personal knowledge management in collaborative environments
Authors:Lu Zhen  Hai-Tao Song  Jun-Tao He
Affiliation:1. Department of Chemistry and Applied Biosciences, ETH Zürich, 8093 Zürich, Switzerland;2. Centro de Investigación en Matemáticas A.C., Jalisco S/N, Mineral y Valenciana 36240, Guanajuato, Mexico;3. Department of Industrial and Systems Engineering, University at Buffalo, Amherst, NY 14260;4. Department of Chemical Engineering, Universitat Politècnica de Catalunya, Av. Diagonal, 647, E08028 Barcelona, Spain
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.
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