Knowledge Acquisition, Modeling and Management : 11th European Workshop, EKAW'99, Dagstuhl Castle, Germany, May 26-29, 1999, Proceedings

Rudi Studer

ISBN 10: 3540660445 / ISBN 13: 9783540660446

Editore: Springer Berlin Heidelberg, 1999

Riguardo questo articolo

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

Dati bibliografici

Titolo: Knowledge Acquisition, Modeling and ...

Casa editrice: Springer Berlin Heidelberg

Data di pubblicazione: 1999

Legatura: Taschenbuch

Condizione: Neu

Descrizione articolo

Riassunto:

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.

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.