{"title":"p图——知识库异常检查的图模型","authors":"Eng Lian Lim, J. McCallum, Kwok-Hung Chan","doi":"10.1109/TAI.1990.130452","DOIUrl":null,"url":null,"abstract":"The authors present a graph model, P-graph, which supports the checking of knowledge bases for anomalies such as deadends, unreachability, cycles, inconsistency, redundancy, subsumption, and missing rules. P-graph captures the essential information needed for anomaly checks. The proposed approach differs from existing research as follows: it checks on groups of problem instances rather than on individual problem instances; it uses empirical knowledge to generate problem instances realizable in practice (only these problem instances need to be checked); and it considers the fact base as part of the knowledge base to be checked.<<ETX>>","PeriodicalId":366276,"journal":{"name":"[1990] Proceedings of the 2nd International IEEE Conference on Tools for Artificial Intelligence","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1990-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"P-graph-a graph model for anomaly checking of knowledge bases\",\"authors\":\"Eng Lian Lim, J. McCallum, Kwok-Hung Chan\",\"doi\":\"10.1109/TAI.1990.130452\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The authors present a graph model, P-graph, which supports the checking of knowledge bases for anomalies such as deadends, unreachability, cycles, inconsistency, redundancy, subsumption, and missing rules. P-graph captures the essential information needed for anomaly checks. The proposed approach differs from existing research as follows: it checks on groups of problem instances rather than on individual problem instances; it uses empirical knowledge to generate problem instances realizable in practice (only these problem instances need to be checked); and it considers the fact base as part of the knowledge base to be checked.<<ETX>>\",\"PeriodicalId\":366276,\"journal\":{\"name\":\"[1990] Proceedings of the 2nd International IEEE Conference on Tools for Artificial Intelligence\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1990-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1990] Proceedings of the 2nd International IEEE Conference on Tools for Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TAI.1990.130452\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1990] Proceedings of the 2nd International IEEE Conference on Tools for Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TAI.1990.130452","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
P-graph-a graph model for anomaly checking of knowledge bases
The authors present a graph model, P-graph, which supports the checking of knowledge bases for anomalies such as deadends, unreachability, cycles, inconsistency, redundancy, subsumption, and missing rules. P-graph captures the essential information needed for anomaly checks. The proposed approach differs from existing research as follows: it checks on groups of problem instances rather than on individual problem instances; it uses empirical knowledge to generate problem instances realizable in practice (only these problem instances need to be checked); and it considers the fact base as part of the knowledge base to be checked.<>