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Comments Classification System using Topic Signature  

Bae, Min-Young (창원대학교 컴퓨터공학과)
Cha, Jeong-Won (창원대학교 컴퓨터공학과)
Publication Information
Journal of KIISE:Software and Applications / v.35, no.12, 2008 , pp. 774-779 More about this Journal
Abstract
In this work, we describe comments classification system using topic signature. Topic signature is widely used for selecting feature in document classification and summarization. Comments are short and have so many word spacing errors, special characters. We firstly convert comments into 7-gram. We consider the 7-gram as sentence. We convert the 7-gram into 3-gram. We consider the 3-gram as word. We select key feature using topic signature and classify new inputs by the Naive Bayesian method. From the result of experiments, we can see that the proposed method is outstanding over the previous methods.
Keywords
comment classification; machine learning; topic signature; n-gram;
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