人工知能学会第二種研究会資料
Online ISSN : 2436-5556
特許文書ベクトルを用いた類似企業の選定
藤原 匠平松本 祐介菅 愛子高橋 大志
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研究報告書・技術報告書 フリー

2019 年 2019 巻 BI-013 号 p. 02-

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The number of M&A and IPO implementations has been increasing year by year, and the capitalmarket has become more active. Along with those situations, when a manager examines M&A and IPO, thecorporate value calculation is an important decision-making index. This paper attempts to improve theaccuracy of selecting similar companies in the process of comparable company analysis and DCF methods.Specifically, Sparse Composite Document Vector (SCDV) was created based on published patentdocuments. Next, similar companies were selected by calculating the distance between companies from thedocument vector made by SCDV.

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