Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Viewing morphology as an inference process
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Analyses of multiple evidence combination
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
A study of thresholding strategies for text categorization
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Experiments on the Use of Feature Selection and Negative Evidence in Automated Text Categorization
ECDL '00 Proceedings of the 4th European Conference on Research and Advanced Technology for Digital Libraries
An extensive empirical study of feature selection metrics for text classification
The Journal of Machine Learning Research
Confidence estimation for NLP applications
ACM Transactions on Speech and Language Processing (TSLP)
Boosting multi-label hierarchical text categorization
Information Retrieval
Introduction to Information Retrieval
Introduction to Information Retrieval
Proceedings of the 10th ACM symposium on Document engineering
Evaluation of normalization techniques in text classification for portuguese
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part III
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There is a commonMathematics SubjectClassification(MSC) System used for categorizing mathematical papers and knowledge. We present results of machine learning of the MSC on full texts of papers in the mathematical digital libraries DML-CZ and NUMDAM. The F1- measure achieved on classification task of top-level MSC categories exceeds 89%. We describe and evaluate our methods for measuring the similarity of papers in the digital library based on paper full texts.