Extracting Irregular Datasets in University Admission Statistics using Text Mining and Benford's Law

Yusuke Tozaki, Takahiko Suzuki, Tsunenori Mine, Sachio Hirokawa

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

抄録

It is known as Benford's law that the distribution of the first digits forms a specific shape for natural numerical datasets. Deviation from the Benford's distribution indicates the irregularity of the dataset. However, it does not tell any clue to interpret the reason of irregularity. The present paper constructs a search engine of cells that appear in tables by correlating a cell with the words in the title of row or column or in the explanation of the table. We generate an exhaustive dataset of cells for testing irregularity by enumerating the search conditions. We applied the method to the number of applicants, the number of candidates, and the number of successful applicants in each department of 565 private universities in Japan. We confirmed the effectiveness of the proposed method by extracting the characteristics of the irregular datasets.

本文言語英語
ホスト出版物のタイトルProceedings - 2019 8th International Congress on Advanced Applied Informatics, IIAI-AAI 2019
出版社Institute of Electrical and Electronics Engineers Inc.
ページ1023-1024
ページ数2
ISBN(電子版)9781728126272
DOI
出版ステータス出版済み - 7 2019
イベント8th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2019 - Toyama, 日本
継続期間: 7 7 20197 11 2019

出版物シリーズ

名前Proceedings - 2019 8th International Congress on Advanced Applied Informatics, IIAI-AAI 2019

会議

会議8th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2019
国/地域日本
CityToyama
Period7/7/197/11/19

All Science Journal Classification (ASJC) codes

  • コンピュータ ネットワークおよび通信
  • コンピュータ サイエンスの応用
  • 情報システム
  • 情報システムおよび情報管理
  • 社会科学(その他)

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