Satoshi Masuda

President of Japan Information Technology Association

Satoshi Masuda is the chairman of the Japan Information Technology Association. He has served as CEO and director of multiple listed companies, including Representative Director of Maruishi Holdings Co., Ltd. and Technical Advisor of Ichiya Co., Ltd. He is in charge of UNSPSC.XBRL at the Tokyo Stock Exchange and TSE Computer Systems Advisor, and is a fintech practical specialist in charge of MSCB.Technical listing, rights offering, and equity finance at the president of International Accounting Office Network BAKERTILLY JAPAN CONSULTING Co., Ltd.

He participated in the launch of UNSPSC by the United Nations, Dun & Bradstreet, and announced a new area of international standard identifier code. His work was published by Tokyo Shoko Research Supervision “Barcode Great Revolution”, United Nations New York Headquarters Official Contract Project United Nations Book Code UNBIS Japanese Electronics Representative, “UN Information Retrieval Glossary”.He has published a dissertation at the Japan Society for Production Management, and is also responsible for joint research in social engineering and information technology engineering in AI. Data Science with Hosei University, Chiba Institute of Technology, Nihon University, Chuo University, and Yamagata University.

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Satoshi Masuda

At present, the programming language itself is replaced by numbers from natural language, and segmentation translation is not compatible, and mistranslation codes are found in specific words and phrases such as colloquial expressions and technical terms. The lack of is noticeable. This translation data uses a corpus consisting of more than 100,000 sentences of video labeling and colloquialism expressed by 20 years of work, and searches the original sentence and the translated sentence by this translator to extract the types. , HPC can be used to build a translation expert data system. Specifically, segmentation by big data AI analysis is extracted and used as a corpus to deep-learn big data such as papers, documents, and nets around the world, and language semantic understanding, empathy, and large-scale knowledge understanding are broadly and deeply visualized by adversarial networks.