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Key Technology Research Text Case Knowledge Base Construction

Author: ZhangWenMing
Tutor: WuJiang
School: Northwestern University
Course: Applied Computer Technology
Keywords: Textual Case Knowledge management Textual Case Knowledge Base Layer Model Integration DN-K-means algorithm
CLC: TP391.1
Type: Master's thesis
Year: 2010
Downloads: 146
Quote: 1
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Abstract


With the development of information technology, knowledge management plays an important role on the development of enterprises and public institution. Textual case knowledge management is a core competitive power of large enterprises, mainly being used on unstructured text case. The structure of textual case base is the precondition of the realization of textual case knowledge management. In view of the existing problem of text case management system, text case knowledge base model and text case clustering algorithm, the model of textual case knowledge base and the textual case clustering algorithm were studied in this thesis.The mainly contributions of this thesis include the following aspects:1) The layers model of textual case knowledge base was proposed in this thesis. From the bottom to up, it mainly include domain knowledge layer, case entity layer and textual case abstract layer textual, which were independent and contact with each other in order to support textual case based reasoning.2) The integration of textual case knowledge base and rules base was proposed in this paper. The domain support function of rules in the TCBR was realized through the conversion between rules and textual case. But the conversion from textual case to rules was achieved by the auxiliary of experts.3) K-means text cluster algorithm based on density and nearest neighbor was put forward in the paper. The selection of initial focal point has a great influence on the clustering results of traditional k-means algorithm, for it tends to get a local optimal solution when inappropriately assigned. In view of this issue, Initial algorithm that can generate the initial cluster centers was proposed, through introducing the density and nearest neighbor idea. These selected centers were used for k-means algorithm; a better text clustering algorithm called DN-k-means was put forward. The results of experiments indicate that the algorithm can lead to results with high and steady clustering quality.4) A textual case knowledge base system called TCKBS was designed and realized to check the theory of textual case knowledge base, the method of integration between textual case knowledge base and rules base, DN-K-means textual case cluster algorithm. The mainly functional modules of TCKBS were explained in the paper.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Text Processing
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