Shkurte Luma-Osmani, F. Ismaili, Xhemal Zenuni, Bujar Raufi
{"title":"因果关联规则挖掘的系统文献综述","authors":"Shkurte Luma-Osmani, F. Ismaili, Xhemal Zenuni, Bujar Raufi","doi":"10.1109/IEMCON51383.2020.9284908","DOIUrl":null,"url":null,"abstract":"As quoted recently, this is the age of information, and for information we need data. Data is everywhere around us and it is expanding dramatically. The aim of this research is to inspect and summarize the state-of-the-art approaches and studies of machine learning methods to causal inference techniques. This review utilizes a systematic literature research to the mostly prominent digital database libraries in the field of computer sciences in recent years. The objective is to identify and investigate three raised research questions to broadly analyze and detailly explore several points of view concerning causal association rules and their application in real-world problems.","PeriodicalId":6871,"journal":{"name":"2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)","volume":"9 1","pages":"0048-0054"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Systematic Literature Review in Causal Association Rules Mining\",\"authors\":\"Shkurte Luma-Osmani, F. Ismaili, Xhemal Zenuni, Bujar Raufi\",\"doi\":\"10.1109/IEMCON51383.2020.9284908\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As quoted recently, this is the age of information, and for information we need data. Data is everywhere around us and it is expanding dramatically. The aim of this research is to inspect and summarize the state-of-the-art approaches and studies of machine learning methods to causal inference techniques. This review utilizes a systematic literature research to the mostly prominent digital database libraries in the field of computer sciences in recent years. The objective is to identify and investigate three raised research questions to broadly analyze and detailly explore several points of view concerning causal association rules and their application in real-world problems.\",\"PeriodicalId\":6871,\"journal\":{\"name\":\"2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)\",\"volume\":\"9 1\",\"pages\":\"0048-0054\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEMCON51383.2020.9284908\",\"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 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEMCON51383.2020.9284908","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Systematic Literature Review in Causal Association Rules Mining
As quoted recently, this is the age of information, and for information we need data. Data is everywhere around us and it is expanding dramatically. The aim of this research is to inspect and summarize the state-of-the-art approaches and studies of machine learning methods to causal inference techniques. This review utilizes a systematic literature research to the mostly prominent digital database libraries in the field of computer sciences in recent years. The objective is to identify and investigate three raised research questions to broadly analyze and detailly explore several points of view concerning causal association rules and their application in real-world problems.