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Myanmar Text Classifier Using Genetic Algorithm

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dc.contributor.author Zaw, Thit Thit
dc.contributor.author Soe, Khin Mar
dc.date.accessioned 2019-10-15T17:22:54Z
dc.date.available 2019-10-15T17:22:54Z
dc.date.issued 2019-03
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/2320
dc.description.abstract Text Classification is the task of automatically assigning a set of documents into certain categories (class or topics) from a predefined set. This also play important role in natural language processing and also crossroad between information retrieval and machine Learning. The dramatic growth of text document in digital form news website make the task of text classification more popular over last ten year. The application of this method can be found in spam filtering, question and answering, language identification. This paper presents the idea of text classification process in term of using machine learning technique and illustrates how Myanmar news documents were classified by applying genetic algorithm. The applied system will be used Myanmar online news articles from Myanmar news website for the purpose of training and testing the system. Term frequency inverse document frequency (tf_idf) algorithm was used to select related feature according to their labelled document which is also applied in many text mining methods. en_US
dc.language.iso en_US en_US
dc.publisher National Journal of Parallel and Soft Computing en_US
dc.relation.ispartofseries Vol-1, Issue-1;
dc.subject Text Mining en_US
dc.subject Text Classification en_US
dc.subject Natural Language Processing en_US
dc.subject Machine Learning en_US
dc.subject Genetic Algorithm en_US
dc.title Myanmar Text Classifier Using Genetic Algorithm en_US
dc.type Article en_US


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