2020年
Indonesian Gender Equality Survey Analysis Using Feature Selection Based Clustering.
11th International Conference on Awareness Science and Technology(iCAST)
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- 開始ページ
- 1
- 終了ページ
- 6
- 記述言語
- 掲載種別
- 研究論文(国際会議プロシーディングス)
- DOI
- 10.1109/iCAST51195.2020.9319480
- 出版者・発行元
- IEEE
This paper presents an analysis of an Indonesian gender equality survey: in 2019, we conducted a survey of attitudes about gender roles in Indonesia and obtained data from 122 individuals. The obtained data were analyzed using our original clustering method (UFVS, Unsupervised Feature Value Selection) to form clusters. The extracted features characterized the clusters and helped to analyze the attitudes of Indonesians towards gender equality. This method allowed the respondents to be grouped by features and each group characteristics could be easily identified. It facilitated the understanding of the survey data.
- リンク情報
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- DOI
- https://doi.org/10.1109/iCAST51195.2020.9319480
- DBLP
- https://dblp.uni-trier.de/rec/conf/icawst/HashimotoSSK20
- URL
- https://dblp.uni-trier.de/rec/conf/icawst/2020
- URL
- https://dblp.uni-trier.de/db/conf/icawst/icawst2020.html#HashimotoSSK20
- Scopus
- https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85100649257&origin=inward
- Scopus Citedby
- https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85100649257&origin=inward
- ID情報
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- DOI : 10.1109/iCAST51195.2020.9319480
- ISBN : 9781728191195
- DBLP ID : conf/icawst/HashimotoSSK20
- SCOPUS ID : 85100649257