Authorship：Lead author   Language：Japanese   Publishing type：Research paper (scientific journal)  

Direct mail using email and social media, in addition to the immediacy of delivery, is widely utilized across various industries due to its convenience, allowing recipients to receive messages on devices such as smartphones. However, the low cost of distribution has led to the normalization of mass email campaigns, and it is also true
that spam emails have become a social issue. A review of previous studies points out the challenge that, when emails are sent frequently, customer satisfaction with the company decreases. As a result, it has been suggested that the optimal frequency for newsletters and similar emails is around once or twice a week. On the other hand,
although empirical studies on the relationship between email delivery frequency and changes in customer satisfaction with the company may have been conducted within companies, these results have largely not been published due to the high confidentiality of the data. The aim of this study is to investigate the relationship
between email delivery frequency and customer atisfaction based on the results of an analysis of real-world data made publicly available on Kaggle.

Authorship：Lead author   Language：Japanese   Publishing type：Research paper (scientific journal)  

In stock investment, the financial condition of a company is one of the critical pieces of information for investors. One practical indicator used to understand a company's financial status is credit ratings, which have been utilized for a long time. This research first describes a method for estimating corporate credit ratings from financial indicators using Support Vector Machines (SVM), a widely used classification technique in the field of machine learning. Next, we discuss some issues associated with existing models and propose improvements to the credit rating estimation model using SVM. Furthermore, we aim to demonstrate the superiority of the proposed model through empirical experiments by applying the method to real data.

Authorship：Lead author   Language：Japanese   Publishing type：Research paper (scientific journal)  

Authorship：Lead author   Language：Japanese   Publishing type：Research paper (scientific journal)  

Authorship：Lead author   Language：Japanese   Publishing type：Research paper (scientific journal)  

Event date： 2024.11

Presentation type：Oral presentation (general)  

Venue：Fukuoka   Country：Japan  

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Event date： 2024.9

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：Tokyo University   Country：Japan  

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