IJAT Vol.12 No.4 pp. 482-491
doi: 10.20965/ijat.2018.p0482


A Study on Support Method of Consulting Service Using Text Mining

Ruriko Watanabe*,†, Nobutada Fujii*, Daisuke Kokuryo*, Toshiya Kaihara*, Yoichi Abe**, and Ryoko Santo***

*Kobe University
1-1 Rokkodai, Nada-ku, Kobe-city, Hyogo 657-8501, Japan

Corresponding author

**F&M, Co., Ltd., Suita, Japan

***The New Industry Research Organization, Kobe, Japan

February 19, 2018
May 24, 2018
Online released:
July 3, 2018
July 5, 2018
text mining, DEA discriminant analysis, correspondence analysis

This study aims to build a support method for consulting service companies allowing them to respond to client demands regardless of the expertise of the consultants. With an emphasis on the revitalization of small and medium-sized enterprises, the importance of support systems for consulting services for small and medium-sized enterprises, which support solving problems that are difficult to deal with by an enterprise, is increasing. Consulting companies can respond to a wide range of management consultations; however, because the contents of a consultation are widely and highly specialized, a service proposal and the problem detection depend on the experience and intuition of the consultant, and thus a stable service may occasionally not be provided. Therefore, a support system for providing stable services independent of the ability of consultants is desired. In this research, as the first step in constructing a support system, an analysis of customer information describing the content of a consultation with the client companies is conducted to predict the occurrence of future problems. Text data such as the consultant’s visitation history, consultation content by e-mail, and call center content are used in the analysis because the contents explain not only the current problems but also possibly contain future problems. This paper describes a method for analyzing the text data by employing text mining. In the proposed method, by combining a correspondence analysis with a DEA (Data Envelopment Analysis) discriminant analysis, words that are strongly related to problem detection are extracted from a large number of words obtained from text data, and variables of the DEA discriminant analysis are reduced and analyzed. The proposed method focuses on a cancellation of contract problems. The cancellation problem does not include uncertainty; it is clearly known whether the contract of the consulting service is being updated or cancelled. In this study, computer experiments were conducted to verify the effectiveness of the proposed method through a comparison with an existing method. The results of the verification experiment are as follows. First, there is a possibility of discovering new factors that cannot be determined from the intuition and experience of the consultant regarding the target problem. Second, through a comparison with the existing method, the effectiveness of the proposed method was confirmed.

Cite this article as:
R. Watanabe, N. Fujii, D. Kokuryo, T. Kaihara, Y. Abe, and R. Santo, “A Study on Support Method of Consulting Service Using Text Mining,” Int. J. Automation Technol., Vol.12 No.4, pp. 482-491, 2018.
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