Document recommendation for knowledge sharing in personal folder environments

Duen-Ren Liu*, Chin Hui Lai, Chiu Wen Huang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


Sharing sustainable and valuable knowledge among knowledge workers is a fundamental aspect of knowledge management. In organizations, knowledge workers usually have personal folders in which they organize and store needed codified knowledge (textual documents) in categories. In such personal folder environments, providing knowledge workers with needed knowledge from other workers' folders is important because it increases the workers' productivity and the possibility of reusing and sharing knowledge. Conventional recommendation methods can be used to recommend relevant documents to workers; however, those methods recommend knowledge items without considering whether the items are assigned to the appropriate category in the target user's personal folders. In this paper, we propose novel document recommendation methods, including content-based filtering and categorization, collaborative filtering and categorization, and hybrid methods, which integrate text categorization techniques, to recommend documents to target worker's personalized categories. Our experiment results show that the hybrid methods outperform the pure content-based and the collaborative filtering and categorization methods. The proposed methods not only proactively notify knowledge workers about relevant documents held by their peers, but also facilitate push-mode knowledge sharing.

Original languageEnglish
Pages (from-to)1377-1388
Number of pages12
JournalJournal of Systems and Software
Issue number8
StatePublished - 1 Aug 2008


  • Document recommendation
  • Knowledge management
  • Knowledge sharing
  • Personal folder
  • Text classification


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