Web Text Classification Using Genetic Algorithm and a Dynamic Neural Network Model
Journal Title: International Journal of Advanced Research in Computer Engineering & Technology(IJARCET) - Year 2013, Vol 2, Issue 2
Abstract
Widespread adoption of the Internet, popularity of social networking, and the digitalization of information within organizations have intensified the need for effective textual document classification algorithms. Most real life classification problems, including text classification is complex and high dimensional in nature. A web text classification method using a dynamic artificial neural network is presented in this paper. The proposed method can classify a set of English text documents into a number of given classes depending on their contents. Text documents, internet edition of news paper, are considered for classification. This paper uses genetic algorithm(GA) for feature engineering, in which most relevant features are extracted and classifies the documents using dynamic neural network, which is an effective and scalable method for text classification
Authors and Affiliations
Revathi N , Anjana Peter , Prof. S. J. K. Jagadeesh Kumar
Keywords
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