Knowledge Mapping Evolution Guided by Data Mining
نویسندگان
چکیده
Preserve knowledge, retain know, these are the objectives of a scalable company. The knowledge mapping is graphical techniques which allows preserve and visualize the strategic heritage of the acquired know-how during the years. We use Data mining techniques to exploit the different sources of data and to improve the process of acquiring this knowledge. In this paper, we present a new knowledge mapping approach based on the one hand, on the Boolean modeling of mapping domains knowledge and on the other hand, the use of different data sources by data mining technique to improve the process of acquiring knowledge explicit. To evaluate our approach, we have initiated a process of mapping guided by machine learning which operates in two stages: a data mining and automatic mapping. Data mining is to run initially from an induction Boolean case studies (explicit knowledge). The mapping rules are then used to automatically improve the Boolean model of the knowledge mapping.
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