{"title":"图论——通过可疑就业数据调查腐败和现代奴隶制的案例","authors":"Felicity Gerry, Joseph R. Barr, Peter Shaw","doi":"10.1109/TransAI49837.2020.00025","DOIUrl":null,"url":null,"abstract":"This poster uses the mathematics of networks in the novel context of corporate reporting of slavery in supply chains as a method to meet corporate obligations to respect human rights. For those corporates considering risks such as liability for slavery in supply chains, using graph theory, which is capable of sampling affinity in data-bases, can ‘value add’ due diligence by scoring identity and veracity.","PeriodicalId":151527,"journal":{"name":"2020 Second International Conference on Transdisciplinary AI (TransAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Graph Theory–The Case for Investigating Corruption and Modern Slavery through Suspicious Employment Data\",\"authors\":\"Felicity Gerry, Joseph R. Barr, Peter Shaw\",\"doi\":\"10.1109/TransAI49837.2020.00025\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This poster uses the mathematics of networks in the novel context of corporate reporting of slavery in supply chains as a method to meet corporate obligations to respect human rights. For those corporates considering risks such as liability for slavery in supply chains, using graph theory, which is capable of sampling affinity in data-bases, can ‘value add’ due diligence by scoring identity and veracity.\",\"PeriodicalId\":151527,\"journal\":{\"name\":\"2020 Second International Conference on Transdisciplinary AI (TransAI)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 Second International Conference on Transdisciplinary AI (TransAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TransAI49837.2020.00025\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 Second International Conference on Transdisciplinary AI (TransAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TransAI49837.2020.00025","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Graph Theory–The Case for Investigating Corruption and Modern Slavery through Suspicious Employment Data
This poster uses the mathematics of networks in the novel context of corporate reporting of slavery in supply chains as a method to meet corporate obligations to respect human rights. For those corporates considering risks such as liability for slavery in supply chains, using graph theory, which is capable of sampling affinity in data-bases, can ‘value add’ due diligence by scoring identity and veracity.
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