C4.5: programs for machine learning
C4.5: programs for machine learning
Inductive learning algorithms and representations for text categorization
Proceedings of the seventh international conference on Information and knowledge management
BoosTexter: A Boosting-based Systemfor Text Categorization
Machine Learning - Special issue on information retrieval
An Evaluation of Statistical Approaches to Text Categorization
Information Retrieval
Maximizing Text-Mining Performance
IEEE Intelligent Systems
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
A Probabilistic Analysis of the Rocchio Algorithm with TFIDF for Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
A news story categorization system
ANLC '88 Proceedings of the second conference on Applied natural language processing
A Linear Least Squares Fit mapping method for information retrieval from natural language texts
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
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One of the most important manager activities is decision-making. Especially in these days, full of different information, it is necessary to distinguish between important and unimportant information. The aim of this paper is to find methods which fulfil criteria put on managerial decision-making process. Usage of text categorisation can significantly lower manager workload. Another aim can be defined as raise of objectivity in decision-making process. Automated processing of text documents can prevent simplifications and generalisation, which allow us to decide on the base of small amount of cases and widen this decision on all cases.