Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
An algorithm for suffix stripping
Readings in information retrieval
Making large-scale support vector machine learning practical
Advances in kernel methods
A re-examination of text categorization methods
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
A vector space model for automatic indexing
Communications of the ACM
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Text classification using string kernels
The Journal of Machine Learning Research
An extensive empirical study of feature selection metrics for text classification
The Journal of Machine Learning Research
Adaptive anti-spam filtering for agglutinative languages: a special case for Turkish
Pattern Recognition Letters
A fuzzy soft set theoretic approach to decision making problems
Journal of Computational and Applied Mathematics
Introduction to Information Retrieval
Introduction to Information Retrieval
Using Intuitionistic Fuzzy Sets in Text Categorization
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Web Document Classification Based on Rough Set
RSFDGrC '07 Proceedings of the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
A Web Text Fuzzy Classification Algorithm on Fuzzy Comprehensive Weighted Evaluation Reasoning
ICICIC '09 Proceedings of the 2009 Fourth International Conference on Innovative Computing, Information and Control
Computers & Mathematics with Applications
An adjustable approach to fuzzy soft set based decision making
Journal of Computational and Applied Mathematics
Text classification with the support of pruned dependency patterns
Pattern Recognition Letters
Text categorization with class-based and corpus-based keyword selection
ISCIS'05 Proceedings of the 20th international conference on Computer and Information Sciences
Texture classification using a novel, soft-set theory based classification algorithm
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
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In this paper, we proposed a new method for Text Categorization based on fuzzy soft set theory so called fuzzy soft set classifier (FSSC). We use fuzzy soft set representation that derived from the bag-of-words representation and define each term as a distinct word in the set of words of the document collection. The FSSC categorize each document by using fuzzy c-means formula for classification, and use fuzzy soft set similarity to measure distance between two documents. We perform the experiments with the standard Reuters-21578 dataset, and using three kind of weigthing such as boolean, term frequency, and term frequency-invert document frequency to compare the performance of FSSC with others four classifier such as kNN, Bayesian, Rocchio, and SVM. We are using precision, recall, F-measure, retun-size, and the running time as a performance evaluation. Result shown that there is no absolute winner. The FSSC has precision, recall, and F-measure lower than SVM, and kNN but FSSC can work faster than both. When compared with the Bayesian and Rocchio, the FSSC works more slowly but has a higher precision and F-measure.