{"title":"三阶概化与系统分类高阶概化的新方法","authors":"R. Neville","doi":"10.1109/IJCNN.2005.1556174","DOIUrl":null,"url":null,"abstract":"Higher-order generalization is a means of categorizing different types of generalization. The paper presents a framework within which higher-order generalization can be evaluated in a detailed and systematic way. Previous research divided generalization into three categories. However, these categories were fuzzy and imprecise. This paper further refines existing definitions by first assigning each category a logical predicate that it must fulfil in order to achieve a specific order (type) of generalization. Then, it breaks the orders down into four different categories in a detailed and systematic way. The paper focuses on early (initial) results; some of the aims have been demonstrated and amplified through the experimental work.","PeriodicalId":365690,"journal":{"name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Third-order generalization and a new approach to systematically categorizing higher-order generalization\",\"authors\":\"R. Neville\",\"doi\":\"10.1109/IJCNN.2005.1556174\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Higher-order generalization is a means of categorizing different types of generalization. The paper presents a framework within which higher-order generalization can be evaluated in a detailed and systematic way. Previous research divided generalization into three categories. However, these categories were fuzzy and imprecise. This paper further refines existing definitions by first assigning each category a logical predicate that it must fulfil in order to achieve a specific order (type) of generalization. Then, it breaks the orders down into four different categories in a detailed and systematic way. The paper focuses on early (initial) results; some of the aims have been demonstrated and amplified through the experimental work.\",\"PeriodicalId\":365690,\"journal\":{\"name\":\"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.\",\"volume\":\"71 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-12-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IJCNN.2005.1556174\",\"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. 2005 IEEE International Joint Conference on Neural Networks, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCNN.2005.1556174","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Third-order generalization and a new approach to systematically categorizing higher-order generalization
Higher-order generalization is a means of categorizing different types of generalization. The paper presents a framework within which higher-order generalization can be evaluated in a detailed and systematic way. Previous research divided generalization into three categories. However, these categories were fuzzy and imprecise. This paper further refines existing definitions by first assigning each category a logical predicate that it must fulfil in order to achieve a specific order (type) of generalization. Then, it breaks the orders down into four different categories in a detailed and systematic way. The paper focuses on early (initial) results; some of the aims have been demonstrated and amplified through the experimental work.