An e-mail analysis method based on text mining techniques

This paper proposes a method employing text mining techniques to analyze e-mails collected at a customer center. The method uses two kinds of domain-dependent knowledge. One is a key concept dictionary manually provided by human experts. The other is a concept relation dictionary automatically acquired by a fuzzy inductive learning algorithm. The method inputs the subject and the body of an e-mail and decides a text class for the e-mail. Also, the method extracts key concepts from e-mails and presents their statistical information. This paper applies the method to three kinds of analysis tasks: a product analysis task, a contents analysis task, and an address analysis task. The results of numerical experiments indicate that acquired concept relation dictionaries correspond to the intuition of operators in the customer center and give highly precise ratios in the classification.

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