Abstract—Knowledge is the strategic resource for the
organization. Knowledge map is an important tool for
knowledge sharing. Providing the personalized knowledge map
based on the preference of users can ease the burden of learning
the knowledge map and facilitate the finding of the required
knowledge. The tagging to documents reflects the user’s
preference of classification. In the paper, the approach to the
personalized knowledge map construction based on the
collaborative tagging is proposed. Firstly, the weight of the tag
in documents is identified. Secondly, the similarity of users on
the preference of classification is defined and then users that
have the similar classification preference are identified to
expand the current user’s preference of personalized
classification. Then the text vector of document and text
similarity is identified. Afterwards, the knowledge is clustered
according to both the personalized classification similarity and
text similarity. Finally, the topics of each cluster are identified.
In the topic identification, both the weight of the term in the text
and the weight of the term in the tags are integrated. The
experiment shows that proposed method is feasible and
performs well.
Index Terms—Knowledge map, knowledge management
systems, personalized knowledge map.
Ming Li and Mengyue Yuan are with School of Business Administration,
China University of Petroleum, China (e-mail: brightliming@outlook.com).
Haitao Xiong is with School of Computer and Information Engineering,
Beijing Technology and Business University, China.
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Cite: Ming Li, Mengyue Yuan, and Haitao Xiong, "An Approach to the Construction of Personalized Knowledge Map Based on Collaborative Tagging," International Journal of Knowledge Engineering vol. 1, no. 3, pp. 209-213, 2015.
