A Concept Similarity Based Text Classification Algorithm

Authors:
Jing Peng;Dong-qing Yang;Shi-Wei Tang;Jun Gao;Peng-yi Zhang;Yan Fu
Affiliations:
Peking University, Beijing 100871, China;Peking University, Beijing 100871, China;Peking University, Beijing 100871, China;Peking University, Beijing 100871, China;Peking University, Beijing 100871, China;Peking University, Beijing 100871, China
Venue:
FSKD '07 Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01
Year:
2007

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Abstract

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.