Shuo Wang, J. Ren, Hao Fang, Jun Pan, Xin Hu, Tingyun Zhao
{"title":"An advanced algorithm for discrimination prevention in data mining","authors":"Shuo Wang, J. Ren, Hao Fang, Jun Pan, Xin Hu, Tingyun Zhao","doi":"10.1109/TOCS56154.2022.10015960","DOIUrl":null,"url":null,"abstract":"Data mining has been effectively utilized in huge expanded application areas. Associations overall go with significant business choices in light of mining of data. Discrimination in navigation and preservation of protection of data are a couple of significant difficulties in data mining. Discrimination is of two sorts, Direct Discrimination and Indirect Discrimination. Discrimination prevention includes two significant angles disclosure of direct and additionally roundabout discrimination and data transformation as alteration of separating rules without influencing data quality. Existing strategies for discrimination prevention utilize one of the three methodologies, in particular, the pre-process, in-process or post-process approach. Tests for the exhibition assessment of all calculations by fluctuating these info boundaries, each in turn to review and break down impact of these boundaries.","PeriodicalId":227449,"journal":{"name":"2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TOCS56154.2022.10015960","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Data mining has been effectively utilized in huge expanded application areas. Associations overall go with significant business choices in light of mining of data. Discrimination in navigation and preservation of protection of data are a couple of significant difficulties in data mining. Discrimination is of two sorts, Direct Discrimination and Indirect Discrimination. Discrimination prevention includes two significant angles disclosure of direct and additionally roundabout discrimination and data transformation as alteration of separating rules without influencing data quality. Existing strategies for discrimination prevention utilize one of the three methodologies, in particular, the pre-process, in-process or post-process approach. Tests for the exhibition assessment of all calculations by fluctuating these info boundaries, each in turn to review and break down impact of these boundaries.