Knowledge Acquisition, Modeling and Management: 11th European Workshop, EKAW'99, Dagstuhl Castle, Germany, May 26-29, 1999, Proceedings: 1621 - Brossura
Sinossi
Past, Present, and Future of Knowledge Acquisition This book contains the proceedings of the 11th European Workshop on Kno- edge Acquisition, Modeling, and Management (EKAW 99), held at Dagstuhl Castle (Germany) in May of 1999. This continuity and the high number of s- missions re?ect the mature status of the knowledge acquisition community. Knowledge Acquisition started as an attempt to solve the main bottleneck in developing expert systems (now called knowledge-based systems): Acquiring knowledgefromahumanexpert. Variousmethodsandtoolshavebeendeveloped to improve this process. These approaches signi?cantly reduced the cost of - veloping knowledge-based systems. However, these systems often only partially ful?lled the taskthey weredevelopedfor andmaintenanceremainedanunsolved problem. This required a paradigm shift that views the development process of knowledge-based systems as a modeling activity. Instead of simply transf- ring human knowledge into machine-readable code, building a knowledge-based system is now viewed as a modeling activity. A so-called knowledge model is constructed in interaction with users and experts. This model need not nec- sarily re?ect the already available human expertise. Instead it should provide a knowledgelevelcharacterizationof the knowledgethat is requiredby the system to solve the application task. Economy and quality in system development and maintainability are achieved by reusable problem-solving methods and onto- gies. The former describe the reasoning process of the knowledge-based system (i. e. , the algorithms it uses) and the latter describe the knowledge structures it uses (i. e. , the data structures). Both abstract from speci?c application and domain speci?c circumstances to enable knowledge reuse.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Contenuti
Invited Papers.- Reengineering and Knowledge Management.- Knowledge Navigation in Networked Digital Libraries.- Long Papers.- Towards Brokering Problem-Solving Knowledge on the Internet.- TERMINAE: A Linguistics-Based Tool for the Building of a Domain Ontology.- Applications of Knowledge Acquisition in Experimental Software Engineering.- Acquiring and Structuring Web Content with Knowledge Level Models.- A Knowledge-Based News Server Supporting Ontology-Driven Story Enrichment and Knowledge Retrieval.- Modeling Information Sources for Information Integration.- Ontological Reengineering for Reuse.- Formally Verifying Dynamic Properties of Knowledge Based Systems.- Integration of Behavioural Requirements Specification within Knowledge Engineering.- Towards an Ontology for Substances and Related Actions.- Use of Formal Ontologies to Support Error Checking in Specifications.- The Ontologies of Semantic and Transfer Links.- Distributed Problem Solving Environment Dedicated to DNA Sequence Annotation.- Knowledge Acquisition from Multiple Experts Based on Semantics of Concepts.- Acquiring Expert Knowledge for the Design of Conceptual Information Systems.- A Constraint-Based Approach to the Description of Competence.- Short Papers.- Holism and Incremental Knowledge Acquisition.- Indexing Problem Solving Methods for Reuse.- Software Methodologies at Risk.- Knowledge acquisition of predicate argument structures from technical texts using Machine Learning: the system Asium.- An Interoperative Environment for Developing Expert Systems.- On the Use of Meaningful Names in Knowledge-Based Systems.- FMR: An Incremental Knowledge Acquisition System for Fuzzy Domains.- Applying SeSKA to Sisyphus III.- Describing Similar Control Flows for Families of Problem-Solving Methods.- Meta Knowledge for Extending Diagnostic Consultation to Critiquing Systems.- Exploitation of XML for Corporate Knowledge Management.- An Oligo-Agents System with Shared Responsibilities for Knowledge Management.- Veri-KoMoD: Verification of Knowledge Models in the Mechanical Design Field.- A Flexible Framework for Uncertain Expertise.- Elicitation of Operational Track Grids.
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Knowledge Acquisition, Modeling and Management: 11th European Workshop, EKAW'99, Dagstuhl Castle, Germany, May 26-29, 1999, Proceedings. Lecture Notes in Artificial Intelligence 1621
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Gr.-8°, Taschenbuch. Condizione: Gut. 404 S., graf. Darst. Gebraucht: guter und sauberer Zustand. Past, Present, and Future of Knowledge Acquisition This book contains the proceedings of the 11th European Workshop on Kno- edge Acquisition, Modeling, and Management (EKAW 99), held at Dagstuhl Castle (Germany) in May of 1999. This continuity and the high number of s- missions re?ect the mature status of the knowledge acquisition community. Knowledge Acquisition started as an attempt to solve the main bottleneck in developing expert systems (now called knowledge-based systems): Acquiring knowledgefromahumanexpert. Variousmethodsandtoolshavebeendeveloped to improve this process. These approaches signi?cantly reduced the cost of - veloping knowledge-based systems. However, these systems often only partially ful?lled the taskthey weredevelopedfor andmaintenanceremainedanunsolved problem. This required a paradigm shift that views the development process of knowledge-based systems as a modeling activity. Instead of simply transf- ring human knowledge into machine-readable code, building a knowledge-based system is now viewed as a modeling activity. A so-called knowledge model is constructed in interaction with users and experts. This model need not nec- sarily re?ect the already available human expertise. Instead it should provide a knowledgelevelcharacterizationof the knowledgethat is requiredby the system to solve the application task. Economy and quality in system development and maintainability are achieved by reusable problem-solving methods and onto- gies. The former describe the reasoning process of the knowledge-based system (i. e. , the algorithms it uses) and the latter describe the knowledge structures it uses (i. e. , the data structures). Both abstract from speci?c application and domain speci?c circumstances to enable knowledge reuse. Sprache: Englisch Gewicht in Gramm: 518. Codice articolo 81930
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Knowledge Acquisition, Modeling and Management
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Paperback. Condizione: New. 1999 ed. This book constitutes the refereed proceedings of the 11th European Workshop on Knowledge Acquisition, Modeling and Management, EKAW '99, held at Dagstuhl Castle, Germany in May 1999. The volume presents 16 revised full papers and 15 revised short papers were carefully reviewed and selected form a high number of submissions. Also included are two invited papers. The papers address issues of knowledge acquisition (i.e., the process of extracting, creating, structuring knowledge, etc.), of knowledge-level modeling for knowledge-based systems, and of applying and redefining this work in a knowledge management and knowledge engineering context. Codice articolo LU-9783540660446
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Knowledge Acquisition, Modeling and Management
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Past, Present, and Future of Knowledge Acquisition This book contains the proceedings of the 11th European Workshop on Kno- edge Acquisition, Modeling, and Management (EKAW '99), held at Dagstuhl Castle (Germany) in May of 1999. This continuity and the high number of s- missions re ect the mature status of the knowledge acquisition community. Knowledge Acquisition started as an attempt to solve the main bottleneck in developing expert systems (now called knowledge-based systems): Acquiring knowledgefromahumanexpert. Variousmethodsandtoolshavebeendeveloped to improve this process. These approaches signi cantly reduced the cost of - veloping knowledge-based systems. However, these systems often only partially ful lled the taskthey weredevelopedfor andmaintenanceremainedanunsolved problem. This required a paradigm shift that views the development process of knowledge-based systems as a modeling activity. Instead of simply transf- ring human knowledge into machine-readable code, building a knowledge-based system is now viewed as a modeling activity. A so-called knowledge model is constructed in interaction with users and experts. This model need not nec- sarily re ect the already available human expertise. Instead it should provide a knowledgelevelcharacterizationof the knowledgethat is requiredby the system to solve the application task. Economy and quality in system development and maintainability are achieved by reusable problem-solving methods and onto- gies. The former describe the reasoning process of the knowledge-based system (i. e. , the algorithms it uses) and the latter describe the knowledge structures it uses (i. e. , the data structures). Both abstract from speci c application and domain speci c circumstances to enable knowledge reuse. 424 pp. Englisch. Codice articolo 9783540660446
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Past, Present, and Future of Knowledge Acquisition This book contains the proceedings of the 11th European Workshop on Kno- edge Acquisition, Modeling, and Management (EKAW ¿99), held at Dagstuhl Castle (Germany) in May of 1999. This continuity and the high number of s- missions re ect the mature status of the knowledge acquisition community. Knowledge Acquisition started as an attempt to solve the main bottleneck in developing expert systems (now called knowledge-based systems): Acquiring knowledgefromahumanexpert. Variousmethodsandtoolshavebeendeveloped to improve this process. These approaches signi cantly reduced the cost of - veloping knowledge-based systems. However, these systems often only partially ful lled the taskthey weredevelopedfor andmaintenanceremainedanunsolved problem. This required a paradigm shift that views the development process of knowledge-based systems as a modeling activity. Instead of simply transf- ring human knowledge into machine-readable code, building a knowledge-based system is now viewed as a modeling activity. A so-called knowledge model is constructed in interaction with users and experts. This model need not nec- sarily re ect the already available human expertise. Instead it should provide a knowledgelevelcharacterizationof the knowledgethat is requiredby the system to solve the application task. Economy and quality in system development and maintainability are achieved by reusable problem-solving methods and onto- gies. The former describe the reasoning process of the knowledge-based system (i. e. , the algorithms it uses) and the latter describe the knowledge structures it uses (i. e. , the data structures). Both abstract from speci c application and domain speci c circumstances to enable knowledge reuse.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 424 pp. Englisch. Codice articolo 9783540660446
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Past, Present, and Future of Knowledge Acquisition This book contains the proceedings of the 11th European Workshop on Kno- edge Acquisition, Modeling, and Management (EKAW '99), held at Dagstuhl Castle (Germany) in May of 1999. This continuity and the high number of s- missions re ect the mature status of the knowledge acquisition community. Knowledge Acquisition started as an attempt to solve the main bottleneck in developing expert systems (now called knowledge-based systems): Acquiring knowledgefromahumanexpert. Variousmethodsandtoolshavebeendeveloped to improve this process. These approaches signi cantly reduced the cost of - veloping knowledge-based systems. However, these systems often only partially ful lled the taskthey weredevelopedfor andmaintenanceremainedanunsolved problem. This required a paradigm shift that views the development process of knowledge-based systems as a modeling activity. Instead of simply transf- ring human knowledge into machine-readable code, building a knowledge-based system is now viewed as a modeling activity. A so-called knowledge model is constructed in interaction with users and experts. This model need not nec- sarily re ect the already available human expertise. Instead it should provide a knowledgelevelcharacterizationof the knowledgethat is requiredby the system to solve the application task. Economy and quality in system development and maintainability are achieved by reusable problem-solving methods and onto- gies. The former describe the reasoning process of the knowledge-based system (i. e. , the algorithms it uses) and the latter describe the knowledge structures it uses (i. e. , the data structures). Both abstract from speci c application and domain speci c circumstances to enable knowledge reuse. Codice articolo 9783540660446
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