AN APPROACH TO EXTRACTING TEXT CLASSIFICATION DECISION RULES BASED ONINCOMPLETE INFORMATION SYSTEMS

摘要

The extraction and optimization of a Text classification rules is the main indicator to evaluate the ability to adapt and classify of a Text classification system.Based on rough sets and fuzzy clustering theory of text classification system,along with the theory of incomplete information system,the paper presents the method to extract and optimize a classification rule.After experimenting and analysis,it raises satisfaction reduction rules to users,and makes users so quickly to classification the new text,it does enhance the ability to adapt and classify of the system.