Extraction of Relevant Companies from Multiple Companies and Classification Based on Business
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- TANAKA Miryu
- Seikei University
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- SAKAI Hiroyuki
- Seikei University
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- SAKAJI Hiroki
- The University of Tokyo
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- KITAJIMA Ryozo
- Seikei University
Bibliographic Information
- Other Title
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- 複数企業からの関連企業の抽出と事業内容に基づく分類
- フクスウ キギョウ カラ ノ カンレン キギョウ ノ チュウシュツ ト ジギョウ ナイヨウ ニ モトズク ブンルイ
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Abstract
<p>In this paper, as part of application of text mining in companies, we propose a method that extracts new relevant companies by using common elements estimated from multiple customer companies. For example, if the multiple customer companies are “Canon”, “Epson” and “Brother Industries”, our method extracts “printer” and “inkjet” as common elements. Then, our method extracts “Ricoh” and “Roland DG” as new relevant companies by using these common elements. Our method estimates the common elements based on important words extracted from PDF files of the summary of financial statements of companies. Then, our method extracts new relevant companies by using the common elements. Furthermore, our method classifies extracted new relevant companies as company directly related the common elements or company indirectly related the common elements.</p>
Journal
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- Journal of Japan Society for Fuzzy Theory and Intelligent Informatics
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Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 31 (1), 546-562, 2019-02-15
Japan Society for Fuzzy Theory and Intelligent Informatics
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Keywords
Details 詳細情報について
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- CRID
- 1390282763099548288
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- NII Article ID
- 130007595445
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- NII Book ID
- AA1181479X
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- ISSN
- 18817203
- 13477986
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- NDL BIB ID
- 029528938
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed