Abstract
In organizations, knowledge workers usually have their own personal folders that store and organize needed codified knowledge (textual documents) in taxonomy. In such personal folder environments, providing knowledge workers needed knowledge from other workers' folders is important to facilitate knowledge sharing. This work adopts recommendation techniques to provide knowledge workers needed textual documents from other workers folders. Experiments are conducted to verify the performance of various methods using data collected from a research institute laboratory. The result shows that the CBF approach outperforms other methods.
Original language | English |
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Pages (from-to) | 528-532 |
Number of pages | 5 |
Journal | Proceedings of the International Conference on Electronic Business (ICEB) |
State | Published - Dec 2005 |
Event | 5th International Conference on Electronic Business, ICEB 2005 - Hong Kong, Hong Kong Duration: 5 Dec 2005 → 9 Dec 2005 |
Keywords
- Collaborative filtering
- Content-based filtering
- Document recommendation
- Knowledge management