AN INTEGRATED GENERIC TEXT CLASSIFICATION ALGORITHM FOR INDONESIAN AND MALAY NEWS DOCUMENTS

• Main Author: ,, ZUL INDRA
• Format: Thesis
• Language: English
• Published: 2016
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://utpedia.utp.edu.my/id/eprint/21420/1/2015%20-IT%20-%20AN%20INTEGRATED%20GENERIC%20TEXT%20CLASSIFICATION%20ALGORITHM%20FOR%20INDONESIAN%20AND%20MALAY%20NEWS%20DOCUMENT%20-%20ZUL%20INDRA%20-%20MASTER.pdf; http://utpedia.utp.edu.my/id/eprint/21420/

Text classification (TC)provides a better wayto organize information since it allows better understanding and interpretation of the content. It deals with the assignment of labels into a group of similar textual document. However, TC research for Asian language documents is relatively limited compared to English documents and even lesser particularly for news articles. Apart from that, TC research to classify textual documents in similar morphology such Indonesian and Malay is still scarce. Hence, the aimof this study is to develop an integrated generic TCalgorithm which is able to identify the language and then classify the category for identified news documents. Furthermore, top-ra feature selection method is utilised to improve TCperformance andto overcome theonline news corpora classification challenges: rapid datagrowth of online news documents, and the high computational time.