{"title":"使用多标准、多利益相关者方法评估专家系统","authors":"D. Conrath, R. Sharma","doi":"10.1109/DMESP.1991.171731","DOIUrl":null,"url":null,"abstract":"Test results of an approach to evaluating the quality of expert systems are presented. The solution proposed is a multiple-criteria- and multiple-stakeholder-based subjective assessment technique. Its validity was established by conducting field tests with operational expert systems at 19 sites in the North American insurance industry. The results indicate that such a socio-technical approach to evaluating expert systems is a promising alternative to current ad hoc and anecdotal practices. It is the long-term goal of such a line of investigation to produce a diagnostic tool that would serve to support feedback in the knowledge engineering life cycle.<<ETX>>","PeriodicalId":117336,"journal":{"name":"[1991] Proceedings of the IEEE/ACM International Conference on Developing and Managing Expert System Programs","volume":"235 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Evaluating expert systems using a multiple-criteria, multiple-stakeholder approach\",\"authors\":\"D. Conrath, R. Sharma\",\"doi\":\"10.1109/DMESP.1991.171731\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Test results of an approach to evaluating the quality of expert systems are presented. The solution proposed is a multiple-criteria- and multiple-stakeholder-based subjective assessment technique. Its validity was established by conducting field tests with operational expert systems at 19 sites in the North American insurance industry. The results indicate that such a socio-technical approach to evaluating expert systems is a promising alternative to current ad hoc and anecdotal practices. It is the long-term goal of such a line of investigation to produce a diagnostic tool that would serve to support feedback in the knowledge engineering life cycle.<<ETX>>\",\"PeriodicalId\":117336,\"journal\":{\"name\":\"[1991] Proceedings of the IEEE/ACM International Conference on Developing and Managing Expert System Programs\",\"volume\":\"235 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1991] Proceedings of the IEEE/ACM International Conference on Developing and Managing Expert System Programs\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DMESP.1991.171731\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1991] Proceedings of the IEEE/ACM International Conference on Developing and Managing Expert System Programs","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DMESP.1991.171731","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Evaluating expert systems using a multiple-criteria, multiple-stakeholder approach
Test results of an approach to evaluating the quality of expert systems are presented. The solution proposed is a multiple-criteria- and multiple-stakeholder-based subjective assessment technique. Its validity was established by conducting field tests with operational expert systems at 19 sites in the North American insurance industry. The results indicate that such a socio-technical approach to evaluating expert systems is a promising alternative to current ad hoc and anecdotal practices. It is the long-term goal of such a line of investigation to produce a diagnostic tool that would serve to support feedback in the knowledge engineering life cycle.<>