{"title":"根据用户的专业知识和领域知识水平定制解释","authors":"E. Sarantinos, P. Johnson","doi":"10.1109/TAI.1990.130330","DOIUrl":null,"url":null,"abstract":"Two empirical studies and an analysis of natural dialogues between experts, novices and partial experts are given. From this analysis, a theory of explanation dialogues, called EST is developed. In EST, questions are interpreted by combining information from different, semantically related question types which together best capture the essence and meaning of the question. This theory is then applied to the design of an architecture and computational model of interpreting questions and generating explanations. The expert system, named EXPLAIN understands the nature of the question and is able to take account of the previous dialogue. Also, the system can tailor its responses to an individual user's characteristics, including level of expertise and depth of knowledge in the domain.<<ETX>>","PeriodicalId":366276,"journal":{"name":"[1990] Proceedings of the 2nd International IEEE Conference on Tools for Artificial Intelligence","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1990-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Tailoring explanations to the user's level of expertise and domain knowledge\",\"authors\":\"E. Sarantinos, P. Johnson\",\"doi\":\"10.1109/TAI.1990.130330\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Two empirical studies and an analysis of natural dialogues between experts, novices and partial experts are given. From this analysis, a theory of explanation dialogues, called EST is developed. In EST, questions are interpreted by combining information from different, semantically related question types which together best capture the essence and meaning of the question. This theory is then applied to the design of an architecture and computational model of interpreting questions and generating explanations. The expert system, named EXPLAIN understands the nature of the question and is able to take account of the previous dialogue. Also, the system can tailor its responses to an individual user's characteristics, including level of expertise and depth of knowledge in the domain.<<ETX>>\",\"PeriodicalId\":366276,\"journal\":{\"name\":\"[1990] Proceedings of the 2nd International IEEE Conference on Tools for Artificial Intelligence\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1990-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"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.1990.130330\",\"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.1990.130330","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Tailoring explanations to the user's level of expertise and domain knowledge
Two empirical studies and an analysis of natural dialogues between experts, novices and partial experts are given. From this analysis, a theory of explanation dialogues, called EST is developed. In EST, questions are interpreted by combining information from different, semantically related question types which together best capture the essence and meaning of the question. This theory is then applied to the design of an architecture and computational model of interpreting questions and generating explanations. The expert system, named EXPLAIN understands the nature of the question and is able to take account of the previous dialogue. Also, the system can tailor its responses to an individual user's characteristics, including level of expertise and depth of knowledge in the domain.<>
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