Topic Feature Extraction Method Based on Association Rule and Rough Set
Yan Sun · Jisuanji gongcheng · 2012
Aiming at the characteristic that topic classification lacks training samples and has similar topics,this paper proposes a topic feature extracting method based on association rule and rough set.The method uses associated rules mining to generate rules set and text topic,finds different particle levels of topic by regulating the minimum support and minimum confidence of subject matters,and reduces attributes by Vector Space Model(VSM) combined with rough set.Experimental result shows that the method can preferably mine the text topic,and prompt the precise rate in topic classification.