Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
A Validity Measure for Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
A comparison of classifiers and document representations for the routing problem
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Inductive learning algorithms and representations for text categorization
Proceedings of the seventh international conference on Information and knowledge management
Hierarchical classification of Web content
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
Learning to Classify Text Using Support Vector Machines: Methods, Theory and Algorithms
Learning to Classify Text Using Support Vector Machines: Methods, Theory and Algorithms
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Knowledge Representation in Fuzzy Logic
IEEE Transactions on Knowledge and Data Engineering
Maximizing Text-Mining Performance
IEEE Intelligent Systems
Naive (Bayes) at Forty: The Independence Assumption in Information Retrieval
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Hierarchically Classifying Documents Using Very Few Words
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Transductive Inference for Text Classification using Support Vector Machines
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Text classification using string kernels
The Journal of Machine Learning Research
Support vector machines classification with a very large-scale taxonomy
ACM SIGKDD Explorations Newsletter - Natural language processing and text mining
Introduction to Data Mining, (First Edition)
Introduction to Data Mining, (First Edition)
Expert Systems with Applications: An International Journal
Fuzzy support vector machine for multi-class text categorization
Information Processing and Management: an International Journal
Supervised document classification based upon domain-specific term taxonomies
International Journal of Metadata, Semantics and Ontologies
Introduction to Information Retrieval
Introduction to Information Retrieval
SVM Fuzzy Hierarchical Classification Method for Multi-class Problems
WAINA '09 Proceedings of the 2009 International Conference on Advanced Information Networking and Applications Workshops
Feature selection: a useful preprocessing step
IRSG'97 Proceedings of the 19th Annual BCS-IRSG conference on Information Retrieval Research
Projected-prototype based classifier for text categorization
Knowledge-Based Systems
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In this paper we present a new fuzzy classification method based on Support Vector Machine (FHCSVM-Text) to treat categorization document problem. In context of document categorization, we have to separate large number of classes. SVM becomes an important machine learning tool to handle categorization document problem. Usually, SVM classifier is implemented to treat binary classification problem. In order to handle multi-class problems, we present a new method to build dynamically a fuzzy hierarchical structure from the training data. Our method consists in gathering the similar documents in the same class from the root until leaves, based on its textual content. The original problem is divided into sub-problems. The proposed method consists of three steps : (i) Preprocessing step to reduce the large number of features (ii) Fuzzy hierarchical classification (iii) and introducing SVM classifier at each node of the hierarchy. The fuzzy hierarchical structure extracts the fuzzy relationships between deferent classes. Our experimental results improve high accuracy in the Reuters corpus face standard document categorization techniques.