{"title":"基于张量的多维数据挖掘","authors":"Ryohei Yokobayashi, T. Miura","doi":"10.1109/ICDMW.2018.00164","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a data manipulation method to extract multidimensional association rules in the framework of Tensor Data Model (TDM). By using the TDM, high order data structure and naive description for information retrieval are possible. Among others, we discuss multidimensional association rule mining here. Usually, association rule mining (or extraction of association rules) concerns about co-related transaction records of single predicate, and hard to examine the ones over multiple predicates since it takes heavy time-and space-complexities. Here, several operations specific to multidimensional data mining to reduce amount of description can be modeled by using TDM.","PeriodicalId":259600,"journal":{"name":"2018 IEEE International Conference on Data Mining Workshops (ICDMW)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Multidimensional Data Mining Based on Tensor\",\"authors\":\"Ryohei Yokobayashi, T. Miura\",\"doi\":\"10.1109/ICDMW.2018.00164\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a data manipulation method to extract multidimensional association rules in the framework of Tensor Data Model (TDM). By using the TDM, high order data structure and naive description for information retrieval are possible. Among others, we discuss multidimensional association rule mining here. Usually, association rule mining (or extraction of association rules) concerns about co-related transaction records of single predicate, and hard to examine the ones over multiple predicates since it takes heavy time-and space-complexities. Here, several operations specific to multidimensional data mining to reduce amount of description can be modeled by using TDM.\",\"PeriodicalId\":259600,\"journal\":{\"name\":\"2018 IEEE International Conference on Data Mining Workshops (ICDMW)\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Conference on Data Mining Workshops (ICDMW)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDMW.2018.00164\",\"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 IEEE International Conference on Data Mining Workshops (ICDMW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDMW.2018.00164","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we propose a data manipulation method to extract multidimensional association rules in the framework of Tensor Data Model (TDM). By using the TDM, high order data structure and naive description for information retrieval are possible. Among others, we discuss multidimensional association rule mining here. Usually, association rule mining (or extraction of association rules) concerns about co-related transaction records of single predicate, and hard to examine the ones over multiple predicates since it takes heavy time-and space-complexities. Here, several operations specific to multidimensional data mining to reduce amount of description can be modeled by using TDM.