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Strong Rules Learning Algorithm for Ensemble Text Classification | IEEE Conference Publication | IEEE Xplore

Strong Rules Learning Algorithm for Ensemble Text Classification


Abstract:

Currently, most text classifiers apply machine learning methods, while ignore traditional methods based on classification rules. In this paper, we propose a strong coveri...Show More

Abstract:

Currently, most text classifiers apply machine learning methods, while ignore traditional methods based on classification rules. In this paper, we propose a strong covering algorithm (called SCA) for generating strong classification rules and view the rules-based classifier as a component classifier in the ensemble text classifier. SCA extracts noun phrase to index document based-on our proposed Exhaustive Noun-Phrase Extraction Algorithm. Experimental results show that the ensemble classifier integrating the strong rules achieves an approximately 8% improvement as compared to bi-gram classifier and 15% improvement as compared to the single rule-based classifier.
Date of Conference: 19-22 August 2007
Date Added to IEEE Xplore: 29 October 2007
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Conference Location: Hong Kong, China
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