{"title":"使用伽罗瓦晶格结构学习算法","authors":"R. Godin, R. Missaoui, Hassan Alaoui","doi":"10.1109/TAI.1991.167072","DOIUrl":null,"url":null,"abstract":"An incremental algorithm for updating the Galois lattice is proposed where new objects may be dynamically added by modifying the existing lattice. A large experimental application reveals that adding a new object may be done in time proportional to the number of objects on the average. When there is a fixed upper bound on the number of properties related to an object, which is the case in practical applications, the worst case analysis of the algorithm confirms the experimental observations of linear growth with respect to the number of objects. Algorithms for generating rules from the lattice are also given.<<ETX>>","PeriodicalId":371778,"journal":{"name":"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"73","resultStr":"{\"title\":\"Learning algorithms using a Galois lattice structure\",\"authors\":\"R. Godin, R. Missaoui, Hassan Alaoui\",\"doi\":\"10.1109/TAI.1991.167072\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An incremental algorithm for updating the Galois lattice is proposed where new objects may be dynamically added by modifying the existing lattice. A large experimental application reveals that adding a new object may be done in time proportional to the number of objects on the average. When there is a fixed upper bound on the number of properties related to an object, which is the case in practical applications, the worst case analysis of the algorithm confirms the experimental observations of linear growth with respect to the number of objects. Algorithms for generating rules from the lattice are also given.<<ETX>>\",\"PeriodicalId\":371778,\"journal\":{\"name\":\"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-11-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"73\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TAI.1991.167072\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TAI.1991.167072","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Learning algorithms using a Galois lattice structure
An incremental algorithm for updating the Galois lattice is proposed where new objects may be dynamically added by modifying the existing lattice. A large experimental application reveals that adding a new object may be done in time proportional to the number of objects on the average. When there is a fixed upper bound on the number of properties related to an object, which is the case in practical applications, the worst case analysis of the algorithm confirms the experimental observations of linear growth with respect to the number of objects. Algorithms for generating rules from the lattice are also given.<>