The nature of statistical learning theory
The nature of statistical learning theory
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Improving Minority Class Prediction Using Case-Specific Feature Weights
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Evaluating Boosting Algorithms to Classify Rare Classes: Comparison and Improvements
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Mining product reputations on the Web
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Combining clustering and co-training to enhance text classification using unlabelled data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
One-class svms for document classification
The Journal of Machine Learning Research
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
SMOTE: synthetic minority over-sampling technique
Journal of Artificial Intelligence Research
A novelty detection approach to classification
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Vietnamese Knowledge Base development and exploitation
International Journal of Business Intelligence and Data Mining
Using multi decision tree technique to improving decision tree classifier
International Journal of Business Intelligence and Data Mining
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This paper proposes a method that acquires a more appropriate classification model for a risk search system analysing corporate reputation information included in bulletin board sites. The method inductively acquires the model from textual examples composed of many negative examples and a few positive examples. It selects two kinds of important negative examples by referring to expressions related to a specific label. Here, the label represents the contents of the papers. Finally, the method uses the selected negative examples and all the positive examples to acquire the model. The paper verifies the effectiveness of the method through comparative experiments.