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- W2380455050 abstract "As a tool of data analysis and formalizing for knowledge management,Formal Concept Analysis(FCA) can effective mine knowledge interested for people from lager textual data,and which are held in esteem by many researchers.The premise of FCA is that need a pure and well defined formal context.Extracting characteristic word directly from the text and exploiting document with characteristic words to form textual formal context(TFC),which lead to generating a highly sparse two-dimensional table with a lot of noise.It seriously affects efficiency of building concept lattice and the structure of lattice.Therefore,it is necessary to find an effective method for reducing the textual formal context.Comprehensively considering the nature of textual formal context in this paper,we propose a method named TFC-Reducing for the reduction of textual formal context from the view of semantic distance between attributes and mathematical theory,and give a method for evaluating reduction of textual formal context,named as information losses entropy ILE and semantic coverage SC." @default.
- W2380455050 created "2016-06-24" @default.
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- W2380455050 date "2012-01-01" @default.
- W2380455050 modified "2023-09-24" @default.
- W2380455050 title "TFC-Reducing:An Approach for Reduction of Textual Formal Context Based on Semantic Distance Between Attributes and Rules" @default.
- W2380455050 hasPublicationYear "2012" @default.
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