{"title":"更软的概念意味着更智能的查询","authors":"T. Martin","doi":"10.1109/NAFIPS.2002.1018046","DOIUrl":null,"url":null,"abstract":"The vision of a semantic Web incorporates many aspects which require flexible knowledge representation, learning and reasoning. These include: the mismatch between crisp hierarchical structures and the 'fuzzier\" real world in which objects may have partial membership in classes; notions of approximate equality in data, and semantic equivalence of syntactically different structures; and robustness against inconsistent, missing, partial or incorrect data. In this paper we outline a system which uses concept hierarchies to focus queries. We concentrate on the need to avoid rigid definitions and allow uncertainty in the concept hierarchy, in order to combine diverse data sources.","PeriodicalId":348314,"journal":{"name":"2002 Annual Meeting of the North American Fuzzy Information Processing Society Proceedings. NAFIPS-FLINT 2002 (Cat. No. 02TH8622)","volume":"173 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Softer concepts mean smarter queries\",\"authors\":\"T. Martin\",\"doi\":\"10.1109/NAFIPS.2002.1018046\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The vision of a semantic Web incorporates many aspects which require flexible knowledge representation, learning and reasoning. These include: the mismatch between crisp hierarchical structures and the 'fuzzier\\\" real world in which objects may have partial membership in classes; notions of approximate equality in data, and semantic equivalence of syntactically different structures; and robustness against inconsistent, missing, partial or incorrect data. In this paper we outline a system which uses concept hierarchies to focus queries. We concentrate on the need to avoid rigid definitions and allow uncertainty in the concept hierarchy, in order to combine diverse data sources.\",\"PeriodicalId\":348314,\"journal\":{\"name\":\"2002 Annual Meeting of the North American Fuzzy Information Processing Society Proceedings. NAFIPS-FLINT 2002 (Cat. No. 02TH8622)\",\"volume\":\"173 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-08-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2002 Annual Meeting of the North American Fuzzy Information Processing Society Proceedings. NAFIPS-FLINT 2002 (Cat. No. 02TH8622)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAFIPS.2002.1018046\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2002 Annual Meeting of the North American Fuzzy Information Processing Society Proceedings. NAFIPS-FLINT 2002 (Cat. No. 02TH8622)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAFIPS.2002.1018046","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The vision of a semantic Web incorporates many aspects which require flexible knowledge representation, learning and reasoning. These include: the mismatch between crisp hierarchical structures and the 'fuzzier" real world in which objects may have partial membership in classes; notions of approximate equality in data, and semantic equivalence of syntactically different structures; and robustness against inconsistent, missing, partial or incorrect data. In this paper we outline a system which uses concept hierarchies to focus queries. We concentrate on the need to avoid rigid definitions and allow uncertainty in the concept hierarchy, in order to combine diverse data sources.