Knowledge Acquisition, Modeling and Management : 11th European Workshop, EKAW'99, Dagstuhl Castle, Germany, May 26-29, 1999, Proceedings / edited by Rudi Studer.

Format:

Book

Contributor:

Studer, Rudi, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence ; 1621.

Lecture Notes in Artificial Intelligence ; 1621

Language:

English

Subjects (All):

Artificial intelligence.

Artificial Intelligence.

Local Subjects:

Artificial Intelligence.

Physical Description:

1 online resource (XII, 412 pages).

Edition:

First edition 1999.

Contained In:

Springer eBooks

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1999.

System Details:

text file PDF

Summary:

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.

Contents:

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.

Other Format:

Printed edition:

ISBN:

978-3-540-48775-3

9783540487753

Access Restriction:

Restricted for use by site license.