{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T15:44:14Z","timestamp":1784303054534,"version":"3.55.0"},"reference-count":33,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2020,4,7]],"date-time":"2020-04-07T00:00:00Z","timestamp":1586217600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["17KT0034"],"award-info":[{"award-number":["17KT0034"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>The development of transportation and technology has spread human movements more quickly and widely. As a result, our societies are becoming more complex, composed of people of more diverse races, cultures, religions, and languages. In this study, we focus on the origins of ethnicity while analyzing the background of social members. To track the origin of the ethnicities of which a society is composed, we established a surname-nationality prediction model by learning from a Recurrent Neural Network (RNN) with data recorded by business peoples\u2019 surnames and nationalities to predict nationality with high accuracy through surnames. This study is meaningful because it approaches the social scientific problems of ethnic composition within society through massive data and machine learning: the informatics approach.<\/jats:p>","DOI":"10.3390\/info11040197","type":"journal-article","created":{"date-parts":[[2020,4,8]],"date-time":"2020-04-08T05:59:47Z","timestamp":1586325587000},"page":"197","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Detecting Ethnic Spatial Distribution of Business People Using Machine Learning"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3706-170X","authenticated-orcid":false,"given":"Joomi","family":"Jun","sequence":"first","affiliation":[{"name":"Department of Informatics, The Graduate University for Advanced Studies, SOKENDAI, Tokyo 101-8430, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takayuki","family":"Mizuno","sequence":"additional","affiliation":[{"name":"Department of Informatics, The Graduate University for Advanced Studies, SOKENDAI, Tokyo 101-8430, Japan"},{"name":"Information and Society Research Division, National Institute of Informatics, Tokyo 101-8430, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,4,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1349","DOI":"10.1001\/jama.1997.03550160069041","article-title":"Effects of Age, Sex, and Ethnicity on the Association Between Apolipoprotein E Genotype and Alzheimer Disease: A Meta-analysis","volume":"278","author":"Farrer","year":"2003","journal-title":"JAMA"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1016\/j.atherosclerosis.2015.03.021","article-title":"Genetics of cardiovascular disease: Importance of sex and ethnicity","volume":"241","author":"Stacey","year":"2015","journal-title":"Atherosclerosis"},{"key":"ref_3","unstructured":"Gillborn, D. 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