Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
Classifying news stories using memory based reasoning
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Representation and learning in information retrieval
Representation and learning in information retrieval
An example-based mapping method for text categorization and retrieval
ACM Transactions on Information Systems (TOIS)
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
The nature of statistical learning theory
The nature of statistical learning theory
Cluster-based text categorization: a comparison of category search strategies
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Machine Learning
Feature selection, perceptron learning, and a usability case study for text categorization
Proceedings of the 20th 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
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
Term Weighting in Information Retrieval Using the Term Precision Model
Journal of the ACM (JACM)
An Evaluation of Statistical Approaches to Text Categorization
Information Retrieval
Information Retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Effect of term distributions on centroid-based text categorization
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Informatics and computer science intelligent systems applications
Effects of Term Distributions on Binary Classification
IEICE - Transactions on Information and Systems
Adaptable term weighting framework for text classification
CICLing'11 Proceedings of the 12th international conference on Computational linguistics and intelligent text processing - Volume Part II
Exploiting reference section to classify paper's topics
Proceedings of the International Conference on Management of Emergent Digital EcoSystems
A Non-VSM kNN algorithm for text classification
ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications
Class normalization in centroid-based text categorization
Information Sciences: an International Journal
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In this paper, we present a linear text classification algorithm called CRF. By using category relevance factors, CRF computes the feature vectors of training documents belonging to the same category. Based on these feature vectors, CRF induces the profile vector of each category. For new unlabelled documents, CRF adopts a modified cosine measure to obtain similarities between these documents and categories and assigns them to categories that have the biggest similarity scores. In CRF, it is profile vectors not vectors of all training documents that join in computing the similarities between documents and categories. We evaluated our algorithm on a subset of Reuters-21578 and 20_newsgroups text collections and compared it against k-NN and SVM. Experimental results show that CRF outperforms k-NN and is competitive with SVM.