Knowledge Acquisition最新文献

{"title":"What online machine learning can do for knowledge acquisition—a case study","authors":"Edgar Sommer, K. Morik, Jean-Michel André, M. Uszynski","doi":"10.1006/KNAC.1994.1020","DOIUrl":"https://doi.org/10.1006/KNAC.1994.1020","url":null,"abstract":"Abstract This paper reports on the development of a realistic knowledge-based application using the MOBAL system. Some problems and requirements resulting from industrial-caliber tasks are formulated. A step-by-step account of the construction of a knowledge base for such a task demonstrates how the interleaved use of several learning algorithms in concert with an inference engine and a graphical interface can fulfill those requirements. Design, analysis, revision, refinement and extension of a working model are combined in one incremental process. This illustrates the balanced cooperative modelling approach. The case study is taken from the telecommunications domain and more precisely deals with security management in telecommunications networks. MOBAL would be used as part of a security management tool for acquiring, validating and refining a security policy. The modeling approach is compared with other approaches, such as KADS and stand-alone machine learning.","PeriodicalId":100857,"journal":{"name":"Knowledge Acquisition","volume":"4 1","pages":"435-460"},"PeriodicalIF":0.0,"publicationDate":"1994-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82271659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Configuring problem-solving methods: a CAKE perspective","authors":"M. Hori, Yuichi Nakamura, T. Hama","doi":"10.1006/KNAC.1994.1021","DOIUrl":"https://doi.org/10.1006/KNAC.1994.1021","url":null,"abstract":"Abstract Over the past few years a certain amount of research has been done on ways of configuring problem-solving methods from smaller-grained components. Although frameworks for method configuration have been explored in previous studies, ways of developing and maintaining a library of reusable knowledge have not been fully integrated into the frameworks. The purpose of this paper is to provide a view of bridging the architecture of component assembling and the knowledge contents, on the basis of our experiences in the area of scheduling problems. First, existing component-oriented approaches are briefly reviewed. We then introduce the concept of a computer-aided knowledge engineering (CAKE) environment, which consists of not only processes for constructing knowledge systems, but also processes for developing knowledge libraries to be reused for the prospective systems. The content issues in a class of scheduling problems are pursued in terms of the representation primitives of the task and method, the task-specific components to be configured into problem-solving methods, and the process of obtaining those components. Taking account of the knowledge contents, we explore the architectural issues related to our development environment, and give running examples for the task analysis, component retrieval and component configuration. Finally, we compare related studies on reuse-oriented development environments.","PeriodicalId":100857,"journal":{"name":"Knowledge Acquisition","volume":"5 1","pages":"461-488"},"PeriodicalIF":0.0,"publicationDate":"1994-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82415843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Acquisition and validation of software requirements","authors":"Brigitte Biébow,&nbsp;Sylvie Szulman","doi":"10.1006/knac.1994.1017","DOIUrl":"https://doi.org/10.1006/knac.1994.1017","url":null,"abstract":"<div><p>This paper presents a knowledge-based software engineering tool, DASERT (Detection of Anomalies in Software Engineering Requirements Texts), to acquire and validate functional requirements in natural language. The user describes the functional specifications through informal methods, using graphics with comments in natural language. During this elaboration step the system validates the document by processing the comments semantically to detect ambiguities or inconsistencies. To do so it uses natural language processing and knowledge base engineering.</p><p>DASERT's kernel is a KL-ONE-like semantic network, which helps the semantic parsing of the comments and their semantic representation. This knowledge base is first initialized by the acquisition of the lexical domain knowledge, then progressively enriched with the domain terminology given by the user and with the requirements knowledge extracted from the user's graphics and texts.</p><p>During initialization and enrichment, the network manager validates the knowledge structurally. This ensures the logical consistency of the base which is then checked for inconsistencies and ambiguities specific to the domain of software requirements.</p><p>From a software engineering point of view, the originality of DASERT is that it provides a semantic checking of an informal specification by interpreting the natural language comments. From a knowledge acquisition point of view, DASERT allows acquisition from texts to build the kernel of a knowledge base which is then used to guide the semantic parsing of texts during the acquisition of the specification itself. Moreover, the representation formalism provides a unified view of acquisition and validation.</p></div>","PeriodicalId":100857,"journal":{"name":"Knowledge Acquisition","volume":"6 4","pages":"Pages 343-367"},"PeriodicalIF":0.0,"publicationDate":"1994-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1006/knac.1994.1017","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72109720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Foundations for a methodology for medical KBS development","authors":"Gertjan van Heijst, G. Schreiber, G. Lanzola, Marlo Stefanelli","doi":"10.1006/KNAC.1994.1019","DOIUrl":"https://doi.org/10.1006/KNAC.1994.1019","url":null,"abstract":"Abstract This paper presents the foundations for a methodology for the construction of medical knowledge based systems (KBS). To date, the lack of a methodology that takes into account the typical demands posed by medical environments has hindered the practical application of knowledge technology in medical settings. Our approach views the development process as comprising two activities: the construction of a knowledge level model and the subsequent translation of the model into a computational model in such a way that the connections between the computational structures and their knowledge level counterparts are maintained. The availability of these connections enables a KBS to communicate with domain experts in knowledge level terminology while it can use efficient reasoning techniques for the actual computations. To support the methodology a number of tools have been developed which are described. The approach is illustrated with a scenario in the area of treatment of acute myeloid leukemia.","PeriodicalId":100857,"journal":{"name":"Knowledge Acquisition","volume":"42 1","pages":"395-434"},"PeriodicalIF":0.0,"publicationDate":"1994-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85792236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Acquisition and validation of software requirements","authors":"B. Biebow, Sylvie Szulman","doi":"10.1006/KNAC.1994.1017","DOIUrl":"https://doi.org/10.1006/KNAC.1994.1017","url":null,"abstract":"Abstract This paper presents a knowledge-based software engineering tool, DASERT (Detection of Anomalies in Software Engineering Requirements Texts), to acquire and validate functional requirements in natural language. The user describes the functional specifications through informal methods, using graphics with comments in natural language. During this elaboration step the system validates the document by processing the comments semantically to detect ambiguities or inconsistencies. To do so it uses natural language processing and knowledge base engineering. DASERT's kernel is a KL-ONE-like semantic network, which helps the semantic parsing of the comments and their semantic representation. This knowledge base is first initialized by the acquisition of the lexical domain knowledge, then progressively enriched with the domain terminology given by the user and with the requirements knowledge extracted from the user's graphics and texts. During initialization and enrichment, the network manager validates the knowledge structurally. This ensures the logical consistency of the base which is then checked for inconsistencies and ambiguities specific to the domain of software requirements. From a software engineering point of view, the originality of DASERT is that it provides a semantic checking of an informal specification by interpreting the natural language comments. From a knowledge acquisition point of view, DASERT allows acquisition from texts to build the kernel of a knowledge base which is then used to guide the semantic parsing of texts during the acquisition of the specification itself. Moreover, the representation formalism provides a unified view of acquisition and validation.","PeriodicalId":100857,"journal":{"name":"Knowledge Acquisition","volume":"13 1","pages":"343-368"},"PeriodicalIF":0.0,"publicationDate":"1994-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81975218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The semantics of K BS SF, a language for KBS design","authors":"J. W. Spee, L. I. '. Veld","doi":"10.1006/KNAC.1994.1018","DOIUrl":"https://doi.org/10.1006/KNAC.1994.1018","url":null,"abstract":"Abstract This article exemplifies the semantics of KBSSF, a formal specification language for the design of knowledge based systems. KBSSF has been developed within the context of the ESPRIT II project VITAL—a methodology based workbench for KBS development. A formal specification language shows its value especially in the validation and verification of knowledge based systems. In VITAL this validation and verification also has its impact on the knowledge acquisition, because KBSSF is closely related to graphical primitives representing the conceptual model of the domain. To perform validation and verification, tool support is inevitable. The definition of the language semantics is on its turn a prerequisite for the development of such tools. The KBSSF language combines dynamic knowledge and static knowledge. The dynamic specification, i.e. problem solving behaviour, is specified by means of an imperative language with so called inference operators. The static knowledge specification is composed of logical theories which are a combination of Abstract Data Types and order sorted predicate logic. The inference operators form the link between the dynamic knowledge and the static knowledge, they infer new knowledge from the logic theories. The semantics of KBSSF reflects the distinction in dynamic knowledge and static knowledge. The semantics of the behaviour is described in terms of the Plotkin formalism (Plotkin, 1981), a formalism which describes the semantics in terms of transitions between configurations (machine states). The semantics of the logical theories is described in terms of Herbrand models, which are tailored for order sorted logic with equations, restricted to order sorted Horn clauses. The inference operators are given meaning in terms of these Herbrand models. The coupling between the two semantics is achieved by describing the evaluation of the inference operators as one step transitions in the Plotkin formalism, with the meaning in terms of Herbrand models attached to them. Thus, we show that two different semantic description techniques can be combined in an elegant way, which implies that KBSSF can be given a meaningful and pragmatic semantics, for which support tools can be developed.","PeriodicalId":100857,"journal":{"name":"Knowledge Acquisition","volume":"460 1","pages":"369-394"},"PeriodicalIF":0.0,"publicationDate":"1994-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82973904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The semantics of KBSSF, a language for KBS design","authors":"Jan Willem Spee,&nbsp;Linda In't Veld","doi":"10.1006/knac.1994.1018","DOIUrl":"https://doi.org/10.1006/knac.1994.1018","url":null,"abstract":"Abstract This article exemplifies the semantics of KBSSF, a formal specification language for the design of knowledge based systems. KBSSF has been developed within the context of the ESPRIT II project VITAL—a methodology based workbench for KBS development. A formal specification language shows its value especially in the validation and verification of knowledge based systems. In VITAL this validation and verification also has its impact on the knowledge acquisition, because KBSSF is closely related to graphical primitives representing the conceptual model of the domain. To perform validation and verification, tool support is inevitable. The definition of the language semantics is on its turn a prerequisite for the development of such tools. The KBSSF language combines dynamic knowledge and static knowledge. The dynamic specification, i.e. problem solving behaviour, is specified by means of an imperative language with so called inference operators. The static knowledge specification is composed of logical theories which are a combination of Abstract Data Types and order sorted predicate logic. The inference operators form the link between the dynamic knowledge and the static knowledge, they infer new knowledge from the logic theories. The semantics of KBSSF reflects the distinction in dynamic knowledge and static knowledge. The semantics of the behaviour is described in terms of the Plotkin formalism (Plotkin, 1981), a formalism which describes the semantics in terms of transitions between configurations (machine states). The semantics of the logical theories is described in terms of Herbrand models, which are tailored for order sorted logic with equations, restricted to order sorted Horn clauses. The inference operators are given meaning in terms of these Herbrand models. The coupling between the two semantics is achieved by describing the evaluation of the inference operators as one step transitions in the Plotkin formalism, with the meaning in terms of Herbrand models attached to them. Thus, we show that two different semantic description techniques can be combined in an elegant way, which implies that KBSSF can be given a meaningful and pragmatic semantics, for which support tools can be developed.","PeriodicalId":100857,"journal":{"name":"Knowledge Acquisition","volume":"6 4","pages":"Pages 369-393"},"PeriodicalIF":0.0,"publicationDate":"1994-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1006/knac.1994.1018","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72067884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Foundations for a methodology for medical KBS development","authors":"Gertjan van Heijst,&nbsp;Guus Schreiber,&nbsp;Giordano Lanzola,&nbsp;Marlo Stefanelli","doi":"10.1006/knac.1994.1019","DOIUrl":"https://doi.org/10.1006/knac.1994.1019","url":null,"abstract":"<div><p>This paper presents the foundations for a methodology for the construction of medical knowledge based systems (KBS). To date, the lack of a methodology that takes into account the typical demands posed by medical environments has hindered the practical application of knowledge technology in medical settings. Our approach views the development process as comprising two activities: the construction of a knowledge level model and the subsequent translation of the model into a computational model in such a way that the connections between the computational structures and their knowledge level counterparts are maintained. The availability of these connections enables a KBS to communicate with domain experts in knowledge level terminology while it can use efficient reasoning techniques for the actual computations. To support the methodology a number of tools have been developed which are described. The approach is illustrated with a scenario in the area of treatment of acute myeloid leukemia.</p></div>","PeriodicalId":100857,"journal":{"name":"Knowledge Acquisition","volume":"6 4","pages":"Pages 395-433"},"PeriodicalIF":0.0,"publicationDate":"1994-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1006/knac.1994.1019","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72067890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"What online machine learning can do for knowledge acquisition—a case study","authors":"Edgar Sommer,&nbsp;Katharina Morik,&nbsp;Jean-Michel André,&nbsp;Marc Uszynski","doi":"10.1006/knac.1994.1020","DOIUrl":"https://doi.org/10.1006/knac.1994.1020","url":null,"abstract":"<div><p>This paper reports on the development of a realistic knowledge-based application using the MOBAL system. Some problems and requirements resulting from industrial-caliber tasks are formulated. A step-by-step account of the construction of a knowledge base for such a task demonstrates how the interleaved use of several learning algorithms in concert with an inference engine and a graphical interface can fulfill those requirements. Design, analysis, revision, refinement and extension of a working model are combined in one incremental process. This illustrates the balanced cooperative modelling approach. The case study is taken from the telecommunications domain and more precisely deals with security management in telecommunications networks. MOBAL would be used as part of a security management tool for acquiring, validating and refining a security policy. The modeling approach is compared with other approaches, such as KADS and stand-alone machine learning.</p></div>","PeriodicalId":100857,"journal":{"name":"Knowledge Acquisition","volume":"6 4","pages":"Pages 435-460"},"PeriodicalIF":0.0,"publicationDate":"1994-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1006/knac.1994.1020","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72067891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Apology and correction","authors":"","doi":"10.1006/knac.1994.1022","DOIUrl":"https://doi.org/10.1006/knac.1994.1022","url":null,"abstract":"","PeriodicalId":100857,"journal":{"name":"Knowledge Acquisition","volume":"6 4","pages":"Page 489"},"PeriodicalIF":0.0,"publicationDate":"1994-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1006/knac.1994.1022","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72067892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}