{"title":"数据沼泽的护城河效应","authors":"B. Beaton","doi":"10.1109/AI4I.2018.8665705","DOIUrl":null,"url":null,"abstract":"This work chronicles a strategy that became popular among early data scientists for explaining undesirable research outcomes and research process slowdowns to both themselves and clients.","PeriodicalId":133657,"journal":{"name":"2018 First International Conference on Artificial Intelligence for Industries (AI4I)","volume":"299 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Moat Effects of Data Swamps\",\"authors\":\"B. Beaton\",\"doi\":\"10.1109/AI4I.2018.8665705\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work chronicles a strategy that became popular among early data scientists for explaining undesirable research outcomes and research process slowdowns to both themselves and clients.\",\"PeriodicalId\":133657,\"journal\":{\"name\":\"2018 First International Conference on Artificial Intelligence for Industries (AI4I)\",\"volume\":\"299 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 First International Conference on Artificial Intelligence for Industries (AI4I)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AI4I.2018.8665705\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 First International Conference on Artificial Intelligence for Industries (AI4I)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AI4I.2018.8665705","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This work chronicles a strategy that became popular among early data scientists for explaining undesirable research outcomes and research process slowdowns to both themselves and clients.
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