Comments Classification System using Topic Signature
Min-Young Bae, Jeong-Won Cha · Jeongbo gwahaghoe nonmunji. so'peuteuweeo mich eung'yong · 2008
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.