Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)(2007)
Peking Univ
被引用7|浏览2
摘要
Text classification is an important task of data mining. Existing algorithms, which based on vector space models, does not considered concept similarities among words, so the accuracy of traditional text classification cannot guarantee. To solve the problem, this paper proposes a new text classification algorithm in Chinese text processing based on concept similarity. The contributions of the paper include: (1) proposing a new similarity-computing model between words or sentences based on concept similarity; (2) applying the algorithm successfully in the text classification of WEB news; (3). analyzing the similarity computing formulas systematically in theory; (4).proving that the algorithm has much more accurate than traditional k-NN algorithm in text classification problems through extensive experiments.
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关键词
concept similarity,text classification,Chinese text processing,new text classification algorithm,text classification problem,traditional text classification,traditional k-NN algorithm,similarity computing formulas systematically,new similarity-computing model,WEB news,Concept Similarity,Text Classification Algorithm