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Ontology based Categorization of News Article Documents

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dc.contributor.author Thaw, Phyo Wai
dc.date.accessioned 2019-07-12T04:30:08Z
dc.date.available 2019-07-12T04:30:08Z
dc.date.issued 2010-12-16
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/836
dc.description.abstract Nowadays, the number of electronically available information and knowledge from the internet is rapidly growing. Therefore it becomes difficult to find relevant information users need. The most successful example to organize this mass of information is classifying different text documents according to their topics. Text categorization is a general tool for information retrieval, knowledge management and knowledge discovery. In this paper, ontology based news articles documents categorization is introduced. In the process of categorization the incoming news document is categorized into possible concept(s) from a predefined set of concepts. The ontology provides a hierarchical structure where each concept can be treated as a category. Then news can be retrieved by keyword and concept later. Top down method according to the ontology structure is used for classification. en_US
dc.language.iso en en_US
dc.publisher Fifth Local Conference on Parallel and Soft Computing en_US
dc.title Ontology based Categorization of News Article Documents en_US
dc.type Article en_US


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