Recommender systems for personal knowledge management in collaborative environments

被引：22

作者：

Zhen, Lu ^{[1
]}

Song, Hai-Tao ^{[2
]}

He, Jun-Tao ^{[1
]}

机构：

[1] Shanghai Univ, Sch Management, Shanghai 200444, Peoples R China

[2] State Nucl Power Engn Corp Ltd, Shanghai, Peoples R China

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2012年 / 39卷 / 16期

基金：

中国国家自然科学基金;

关键词：

Knowledge management; Personal knowledge management; Recommender systems; Collaborative environments; MANUFACTURING KNOWLEDGE; DESIGN; INNOVATION;

D O I：

10.1016/j.eswa.2012.04.060

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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. (C) 2012 Elsevier Ltd. All rights reserved.

引用

页码：12536 / 12542

页数：7

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