C4.5: programs for machine learning
C4.5: programs for machine learning
An Evaluation of Statistical Approaches to Text Categorization
Information Retrieval
A statistical learning learning model of text classification for support vector machines
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Information Retrieval
Naive (Bayes) at Forty: The Independence Assumption in Information Retrieval
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Document classification by machine: theory and practice
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 2
GATE: a General Architecture for Text Engineering
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
Binarization approaches to email categorization
ICCPOL'06 Proceedings of the 21st international conference on Computer Processing of Oriental Languages: beyond the orient: the research challenges ahead
Email categorization with tournament methods
NLDB'05 Proceedings of the 10th international conference on Natural Language Processing and Information Systems
Text classification with tournament methods
TSD'05 Proceedings of the 8th international conference on Text, Speech and Dialogue
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This paper presents an adaptive email categorization method developed for the Active Information Management component of the EU FASiL project. The categorization strategy seeks to categorize new emails by learning user preferences, with a feature-balancing algorithm that improves the data training effectiveness and with a dynamic scheduling strategy that achieves the system adaptivity. The results of our evaluation with user-centric corpora constructed automatically from email servers are presented, with around 90% precision consistently being achieved after three months of use. Adaptivity of the system is also evaluated by studying system performance within the continuous three months.