{"title":"基于本体的多维关联规则挖掘","authors":"H. Brahmi","doi":"10.1109/ICOIN.2019.8718172","DOIUrl":null,"url":null,"abstract":"Many approaches have provided applicable solutions to explain associations within data cubes. Nevertheless, there are still many issues causing users extra time to get real knowledge or even failing to obtain the useful knowledge they need. In this paper, we introduce an ontology based approach for multidimensional association rule mining that incorporates a domain ontology to help users in reducing the system resource consumption and improving the efficiency of the mining process. The structure of this ontology is illustrated and how it would be of benefit to the mining process is also demonstrated. Our experimental results prove that a significant improvement and efficiency is achieved using our suggested approach in comparison with those fitting in the same trend.","PeriodicalId":422041,"journal":{"name":"2019 International Conference on Information Networking (ICOIN)","volume":"2008 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Ontology Enhanced Mining of Multidimensional Association Rules from Data Cubes\",\"authors\":\"H. Brahmi\",\"doi\":\"10.1109/ICOIN.2019.8718172\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Many approaches have provided applicable solutions to explain associations within data cubes. Nevertheless, there are still many issues causing users extra time to get real knowledge or even failing to obtain the useful knowledge they need. In this paper, we introduce an ontology based approach for multidimensional association rule mining that incorporates a domain ontology to help users in reducing the system resource consumption and improving the efficiency of the mining process. The structure of this ontology is illustrated and how it would be of benefit to the mining process is also demonstrated. Our experimental results prove that a significant improvement and efficiency is achieved using our suggested approach in comparison with those fitting in the same trend.\",\"PeriodicalId\":422041,\"journal\":{\"name\":\"2019 International Conference on Information Networking (ICOIN)\",\"volume\":\"2008 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Information Networking (ICOIN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOIN.2019.8718172\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Information Networking (ICOIN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOIN.2019.8718172","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Ontology Enhanced Mining of Multidimensional Association Rules from Data Cubes
Many approaches have provided applicable solutions to explain associations within data cubes. Nevertheless, there are still many issues causing users extra time to get real knowledge or even failing to obtain the useful knowledge they need. In this paper, we introduce an ontology based approach for multidimensional association rule mining that incorporates a domain ontology to help users in reducing the system resource consumption and improving the efficiency of the mining process. The structure of this ontology is illustrated and how it would be of benefit to the mining process is also demonstrated. Our experimental results prove that a significant improvement and efficiency is achieved using our suggested approach in comparison with those fitting in the same trend.