Paper Info
Title
An Algorithm of Text Categorization Based on Similar Rough Set and Fuzzy Cognitive Map
Abstract
This paper proposes a new text categorization method based on the similar rough set and the fuzzy cognitive map (FCM). The method replaces casual relation with correlation relation in the fuzzy cognitive map, called correlation-FCM, for constructing text classifiers. Text categorization can be implemented by reasoning approaches based on fuzzy cognitive maps which include weights and correlation degrees. We use similar rough set to generate an efficient representation of documents and apply correlation-FCM for training text classifiers. We apply this proposed method to the WebKB benchmark datasets and the results prove that the method is a good choice for applications with a limited amount of labeled training data. We also demonstrate the effect of changing training size on the classification performance of the learners.
Year
DOI
Venue
2008
10.1109/FSKD.2008.338
FSKD (3)
Keywords
Field
DocType
casual relation,training data,fuzzy cognitive map,new text categorization method,training size,training text classifier,text classifier,text categorization,similar rough set,mutual information,rough set theory,fuzzy set theory,rough set,correlation,classification algorithms,learning artificial intelligence,text analysis,cognition
Text mining,Pattern recognition,Computer science,Fuzzy cognitive map,Fuzzy set,Rough set,Correlation,Artificial intelligence,Mutual information,Cognition,Statistical classification,Machine learning
Conference
Citations 
PageRank 
References 
4
0.39
9
Authors
2
Name
Order
Citations
PageRank
Xin Zhou112615.50
Huaxiang Zhang243656.32