{"title":"KB/RMS:需求定义的智能助手","authors":"R. Binder, J. Tsai","doi":"10.1109/TAI.1990.130407","DOIUrl":null,"url":null,"abstract":"A conceptual framework and a system model for an intelligent assistant for requirement definition, KB/RMS, is presented. The requirement definition process is characterised by the requirements context model. Informal and formal methods for requirement definition are considered in light of this model, which serves as the logical schema for the KB/RMS database. Conventional and knowledge-based system support for requirement definition is summarized. The use of natural language processing, a semantic model of the problem and solution spaces, domain and technology models, and inference-driven augmentation, validation, and verification of the semantic model is discussed. Production of design representations from the augmented semantic model is covered.<<ETX>>","PeriodicalId":366276,"journal":{"name":"[1990] Proceedings of the 2nd International IEEE Conference on Tools for Artificial Intelligence","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1990-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"KB/RMS: an intelligent assistant for requirement definition\",\"authors\":\"R. Binder, J. Tsai\",\"doi\":\"10.1109/TAI.1990.130407\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A conceptual framework and a system model for an intelligent assistant for requirement definition, KB/RMS, is presented. The requirement definition process is characterised by the requirements context model. Informal and formal methods for requirement definition are considered in light of this model, which serves as the logical schema for the KB/RMS database. Conventional and knowledge-based system support for requirement definition is summarized. The use of natural language processing, a semantic model of the problem and solution spaces, domain and technology models, and inference-driven augmentation, validation, and verification of the semantic model is discussed. Production of design representations from the augmented semantic model is covered.<<ETX>>\",\"PeriodicalId\":366276,\"journal\":{\"name\":\"[1990] Proceedings of the 2nd International IEEE Conference on Tools for Artificial Intelligence\",\"volume\":\"52 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1990-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"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.1990.130407\",\"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.1990.130407","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
KB/RMS: an intelligent assistant for requirement definition
A conceptual framework and a system model for an intelligent assistant for requirement definition, KB/RMS, is presented. The requirement definition process is characterised by the requirements context model. Informal and formal methods for requirement definition are considered in light of this model, which serves as the logical schema for the KB/RMS database. Conventional and knowledge-based system support for requirement definition is summarized. The use of natural language processing, a semantic model of the problem and solution spaces, domain and technology models, and inference-driven augmentation, validation, and verification of the semantic model is discussed. Production of design representations from the augmented semantic model is covered.<>
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