An Approach to the Construction of the Personalized Knowledge Map in Knowledge Management Systems

Abstract:

This paper proposes a personalized knowledge map construction method to facilitate knowledge map construction in knowledge management systems. Knowledge map is an important tool in knowledge management systems. Considering the classification habits, the providing of the personalized knowledge map can make the knowledge searching more easily. The tagging reflects the user’s classification habits. Moreover, the words in the tags reflect the user’s word using habits. Therefore, we proposed an approach to the personalized knowledge map construction. Firstly, the documents are pre-processed including eliminating the stop words and stemming the word. Secondly, the KNN algorithm is modified, in which both the vector similarity and the tagging similarity are used to calculate the similarity between the documents. Finally, the topic identification methods of the clusters are proposed. Afterwards, we evaluate the personalized knowledge map construction methods. The results show that the personalized knowledge map gets a good satisfaction.

• Periodical: Applied Mechanics and Materials (Volume 598)
• Pages: 736-739
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.598.736
• Online since: July 2014
• Authors: Ming Li*, Bao Wen Sun, Wei Zhang
• Keywords: KNN, Knowledge Management, Knowledge Map, Knowledge Sharing

References

[1] Quintas, P., Lefrere, P., & Jones, G. (1997). Knowledge management: a strategic agenda. Long range planning, 30(3), 385-391.

DOI: 10.1016/s0024-6301(97)90252-1

[2] Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge management: an organizational capabilities perspective. J. of Management Information Systems, 18(1), 185-214.

DOI: 10.1080/07421222.2001.11045669

[3] Bun, K. K., & Ishizuka, M. (2002, December). Topic extraction from news archive using tf* pdf algorithm. In Web Information Systems Engineering, International Conference on (p.73). IEEE Computer Society.

DOI: 10.1109/wise.2002.1181645

[4] Alavi, M., & Leidner, D. E. (2001). Review: Knowledge management and knowledge management systems: Conceptual foundations and research issues. MIS quarterly, 25(1), 107-136.

DOI: 10.2307/3250961

[5] Luo, C., Li, Y., & Chung, S. M. (2009). Text document clustering based on neighbors. Data & Knowledge Engineering, 68(11), 1271-1288.

DOI: 10.1016/j.datak.2009.06.007

[6] Lin, F. R., & Hsueh, C. M. (2006). Knowledge map creation and maintenance for virtual communities of practice. Information processing & management, 42(2), 551-568.

DOI: 10.1016/j.ipm.2005.03.026

[7] Yoon, B., Lee, S., & Lee, G. (2010). Development and application of a keyword-based knowledge map for effective R&D planning. Scientometrics, 85(3), 803-820.

DOI: 10.1007/s11192-010-0294-5

[8] Kang, I., Park, Y., & Kim, Y. (2003). A framework for designing a workflow-based knowledge map. Business process management journal, 9(3), 281-294.

DOI: 10.1108/14637150310477894

[9] Yang, J. B. (2007). Developing a knowledge map for construction scheduling using a novel approach. Automation in construction, 16(6), 806-815.

DOI: 10.1016/j.autcon.2007.02.005

[10] Xuan, W. F., Liu, B. Q., Sun, C. J., Zhang, D. Y., & Wang, X. L. (2011, July). Finding main topics in blogosphere using document clustering based on topic model. In Machine Learning and Cybernetics (ICMLC), 2011 International Conference on (Vol. 4, pp.1902-1908.

DOI: 10.1109/icmlc.2011.6016947