LEADER 06027oam 2200601 450 001 996465323903316 005 20210715104147.0 010 $a3-540-48775-1 024 7 $a10.1007/3-540-48775-1 035 $a(CKB)1000000000211183 035 $a(SSID)ssj0000324259 035 $a(PQKBManifestationID)11236836 035 $a(PQKBTitleCode)TC0000324259 035 $a(PQKBWorkID)10313779 035 $a(PQKB)11538933 035 $a(DE-He213)978-3-540-48775-3 035 $a(MiAaPQ)EBC3073258 035 $a(MiAaPQ)EBC6485890 035 $a(PPN)155229605 035 $a(EXLCZ)991000000000211183 100 $a20210715d1999 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 00$aKnowledge acquisition, modeling and management $e11th European workshop, EKAW '99, Dagstuhl Castle, Germany, May 26-29, 1999 : proceedings /$fDieter Fensel, Rudi Studer, editors 205 $a1st ed. 1999. 210 1$aBerlin ;$aHeidelberg :$cSpringer Verlag,$d[1999] 210 4$d©1999 215 $a1 online resource (XII, 412 p.) 225 1 $aLecture Notes in Artificial Intelligence ;$v1621 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-66044-5 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aInvited 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. 330 $aPast, Present, and Future of Knowledge Acquisition This book contains the proceedings of the 11th European Workshop on Kno- edge Acquisition, Modeling, and Management (EKAW ?99), held at Dagstuhl Castle (Germany) in May of 1999. This continuity and the high number of s- missions re?ect the mature status of the knowledge acquisition community. Knowledge Acquisition started as an attempt to solve the main bottleneck in developing expert systems (now called knowledge-based systems): Acquiring knowledgefromahumanexpert. Variousmethodsandtoolshavebeendeveloped to improve this process. These approaches signi?cantly reduced the cost of - veloping knowledge-based systems. However, these systems often only partially ful?lled the taskthey weredevelopedfor andmaintenanceremainedanunsolved problem. This required a paradigm shift that views the development process of knowledge-based systems as a modeling activity. Instead of simply transf- ring human knowledge into machine-readable code, building a knowledge-based system is now viewed as a modeling activity. A so-called knowledge model is constructed in interaction with users and experts. This model need not nec- sarily re?ect the already available human expertise. Instead it should provide a knowledgelevelcharacterizationof the knowledgethat is requiredby the system to solve the application task. Economy and quality in system development and maintainability are achieved by reusable problem-solving methods and onto- gies. The former describe the reasoning process of the knowledge-based system (i. e. , the algorithms it uses) and the latter describe the knowledge structures it uses (i. e. , the data structures). Both abstract from speci?c application and domain speci?c circumstances to enable knowledge reuse. 410 0$aLecture Notes in Artificial Intelligence ;$v1621 606 $aKnowledge acquisition (Expert systems)$vCongresses 606 $aDatabase management$vCongresses 615 0$aKnowledge acquisition (Expert systems) 615 0$aDatabase management 676 $a006.33 702 $aFensel$b Dieter 702 $aStuder$b Rudi 712 12$aEuropean Knowledge Acquisition Workshop$d(11th :$f1999 :$eDagstuhl Castle, Germany) 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bUtOrBLW 906 $aBOOK 912 $a996465323903316 996 $aKnowledge Acquisition, Modeling and Management$92088739 997 $aUNISA