Abstract
A text mining system using domain-dependent dictionaries efficiently analyzes text data. The dictionaries store not only impor- tant words for the domains, but also rules composed of some important words. The paper proposes a method that automatically acquires the rules from the text data and their classes by using a fuzzy induc- tive learning method. Also, in order to infer a class corresponding to new text data, the paper proposes an inference method based on the acquired fuzzy decision tree. Moreover, the efficiency of the methods is verified through numerical experiments using more than 1,000 daily business reports concerning retailing.
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Sakurai, S., Ichimura, Y., Suyama, A., Orihara, R. (2001). Inductive learning of a knowledge dictionary for a text mining system. In: Monostori, L., Váncza, J., Ali, M. (eds) Engineering of Intelligent Systems. IEA/AIE 2001. Lecture Notes in Computer Science(), vol 2070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45517-5_28
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DOI: https://doi.org/10.1007/3-540-45517-5_28
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