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Huge amount of data in today's world are stored in the form of electronic documents. Text mining is the process of extracting the information out of those textual documents. Text classification is the process of classifying text documents into fixed number of predefined classes. The application of text classification includes spam filtering, email routing, sentiment analysis, language identification...
The social media generates large volume of data through tweets and text messages during and after any disaster. The analysis and classification of the obtained data at the time of disaster is essential for conveying the information to the appropriate rescue personnel. In this paper, an automated text classification system is proposed in order to classify the data effectively. The classification of...
In text classification, feature selection is essential to improve the classification effectiveness. This paper provides an empirical study of a feature selection method based on genetic algorithms for different text representation methods. This feature selection algorithm can accomplish two goals: in one hand is the search of a feature subset such that the performance of classifier is best; in other...
Machine learning classifiers are widely used for text categorization however a classifier misclassifies some of the instances into a category that is relevant to their actual category. The categorization ability of a classifier can be improved by filtering dataset with better classifier and removing such category for misclassified instances. In this paper we proposed a two level approach where level-1...
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