{"title":"基于差别矩阵的概念格约简比较","authors":"Ling Wei, Jing Zhang, Hongying Zhang","doi":"10.1109/ICMLC.2011.6016909","DOIUrl":null,"url":null,"abstract":"Attribute reduction is an important issue in formal concept analysis, and its efficient reduction algorithm is accordingly important. For two existing lattice reduction methods based on different discernbility matrixes, we give their algorithms and compare their runtime. The experiments show the great difference about these two methods, which reveals that it will be more efficient from the viewpoint of parent-child relation when study the lattice reduction of formal contexts and other relative problems.","PeriodicalId":228516,"journal":{"name":"2011 International Conference on Machine Learning and Cybernetics","volume":"220 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Comparison of concept lattice reduction based on discernbility matrixes\",\"authors\":\"Ling Wei, Jing Zhang, Hongying Zhang\",\"doi\":\"10.1109/ICMLC.2011.6016909\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Attribute reduction is an important issue in formal concept analysis, and its efficient reduction algorithm is accordingly important. For two existing lattice reduction methods based on different discernbility matrixes, we give their algorithms and compare their runtime. The experiments show the great difference about these two methods, which reveals that it will be more efficient from the viewpoint of parent-child relation when study the lattice reduction of formal contexts and other relative problems.\",\"PeriodicalId\":228516,\"journal\":{\"name\":\"2011 International Conference on Machine Learning and Cybernetics\",\"volume\":\"220 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Machine Learning and Cybernetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMLC.2011.6016909\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Machine Learning and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMLC.2011.6016909","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparison of concept lattice reduction based on discernbility matrixes
Attribute reduction is an important issue in formal concept analysis, and its efficient reduction algorithm is accordingly important. For two existing lattice reduction methods based on different discernbility matrixes, we give their algorithms and compare their runtime. The experiments show the great difference about these two methods, which reveals that it will be more efficient from the viewpoint of parent-child relation when study the lattice reduction of formal contexts and other relative problems.