C4.5: programs for machine learning
C4.5: programs for machine learning
Fast discovery of association rules
Advances in knowledge discovery and data mining
An Evaluation of Statistical Approaches to Text Categorization
Information Retrieval
Machine Learning
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Feature selection and feature extraction for text categorization
HLT '91 Proceedings of the workshop on Speech and Natural Language
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
A Recursive Partitioning Decision Rule for Nonparametric Classification
IEEE Transactions on Computers
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Detection of e-mails about criminal activities using association rule-based decision tree is studied here. Instead of using words, word-relation, that is, association rules from these words, is used for building decision tree. In our experiments, we first preprocess data. We then find out association relations among these words using Rakesh Agrawal et al.'s Apriori algorithm applying objective interestingness measures. These rules are used for training and testing the decision tree-based classification system. A discussion of the result obtained is also given.