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In this paper, we propose an automatic clustering method to find synonymous terms including cross-language keywords from Chinese and English thesis documents. First, Chinese and English keyword pairs were collected from an existing database. Then, the system calculates the support and confidence values of the keyword
This paper introduces a new technique of document clustering based on frequent senses. The proposed system, GDClust (graph-based document clustering) works with frequent senses rather than frequent keywords used in traditional text mining techniques. GDClust presents text documents as hierarchical document-graphs and
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