Chun-Hao Chen, Guo-Cheng Lan, T. Hong, Yui-Kai Lin
{"title":"一种高相干关联规则挖掘算法","authors":"Chun-Hao Chen, Guo-Cheng Lan, T. Hong, Yui-Kai Lin","doi":"10.1109/TAAI.2012.51","DOIUrl":null,"url":null,"abstract":"The goal of data mining is to help market managers find relationships among items from large data sets to increase sales volume. The Apriori algorithm is a method for association rule mining, a data mining technique. Although a lot of mining approaches have been proposed based on the Apriori algorithm, most focus on positive association rules, such as \"If milk is bought, then bread is bought\". However, such a rule may be misleading since customers that buy milk may not buy bread. In this paper, an algorithm for mining highly coherent rules that takes the properties of propositional logic into consideration is proposed. The derived association rules may thus be more thoughtful and reliable. Experiments are conducted on simulation data sets to demonstrate the performance of the proposed approach.","PeriodicalId":385063,"journal":{"name":"2012 Conference on Technologies and Applications of Artificial Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A High Coherent Association Rule Mining Algorithm\",\"authors\":\"Chun-Hao Chen, Guo-Cheng Lan, T. Hong, Yui-Kai Lin\",\"doi\":\"10.1109/TAAI.2012.51\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The goal of data mining is to help market managers find relationships among items from large data sets to increase sales volume. The Apriori algorithm is a method for association rule mining, a data mining technique. Although a lot of mining approaches have been proposed based on the Apriori algorithm, most focus on positive association rules, such as \\\"If milk is bought, then bread is bought\\\". However, such a rule may be misleading since customers that buy milk may not buy bread. In this paper, an algorithm for mining highly coherent rules that takes the properties of propositional logic into consideration is proposed. The derived association rules may thus be more thoughtful and reliable. Experiments are conducted on simulation data sets to demonstrate the performance of the proposed approach.\",\"PeriodicalId\":385063,\"journal\":{\"name\":\"2012 Conference on Technologies and Applications of Artificial Intelligence\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Conference on Technologies and Applications of Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TAAI.2012.51\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Conference on Technologies and Applications of Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TAAI.2012.51","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The goal of data mining is to help market managers find relationships among items from large data sets to increase sales volume. The Apriori algorithm is a method for association rule mining, a data mining technique. Although a lot of mining approaches have been proposed based on the Apriori algorithm, most focus on positive association rules, such as "If milk is bought, then bread is bought". However, such a rule may be misleading since customers that buy milk may not buy bread. In this paper, an algorithm for mining highly coherent rules that takes the properties of propositional logic into consideration is proposed. The derived association rules may thus be more thoughtful and reliable. Experiments are conducted on simulation data sets to demonstrate the performance of the proposed approach.