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Journal ArticleDOI

Developing Knowledge-Based Systems with MIKE

TLDR
The paper describes the MIKE (Model-based and Incremental Knowledge Engineering) approach for developing knowledge-based systems, which integrates semiformal and formal specification techniques together with prototyping into a coherent framework.
Abstract
The paper describes the MIKE (Model-based and Incremental Knowledge Engineering) approach for developing knowledge-based systems. MIKE integrates semiformal and formal specification techniques together with prototyping into a coherent framework. All activities in the building process of a knowledge-based system are embedded in a cyclic process model. For the semiformal representation we use a hypermedia-based formalism which serves as a communication basis between expert and knowledge engineer during knowledge acquisition. The semiformal knowledge representation is also the basis for formalization, resulting in a formal and executable model specified in the Knowledge Acquisition and Representation Language (KARL). Since KARL is executable, the model of expertise can be developed and validated by prototyping. A smooth transition from a semiformal to a formal specification and further on to design is achieved because all the description techniques rely on the same conceptual model to describe the functional and nonfunctional aspects of the system. Thus, the system is thoroughly documented at different description levels, each of which focuses on a distinct aspect of the entire development effort. Traceability of requirements is supported by linking the different models to each other.

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Citations
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Journal ArticleDOI

Knowledge engineering: principles and methods

TL;DR: The paradigm shift from a transfer view to a modeling view is discussed and two approaches which considerably shaped research in Knowledge Engineering are described: Role-limiting Methods and Generic Tasks.
Proceedings Article

Overview of Knowledge Sharing and Reuse Components: Ontologies and Problem-Solving Methods

TL;DR: An overview of approaches for ontologies and problem-solving methods is given, which can be viewed as complementary entities that can be used to configure new knowledge systems from existing, reusable components.
Journal ArticleDOI

Structured development of problem solving methods

TL;DR: This paper presents a comprehensive and detailed framework for characterizing problem solving methods and their development process and suggests that PSM development consists of introducing assumptions and commitments along a three-dimensional space defined in terms of problem-solving strategy, task commitments, and domain (knowledge) assumptions.
References
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Journal ArticleDOI

A translation approach to portable ontology specifications

TL;DR: This paper describes a mechanism for defining ontologies that are portable over representation systems, basing Ontolingua itself on an ontology of domain-independent, representational idioms.
Book

Object-Oriented Modeling and Design

TL;DR: This book discusses Object Modeling as a Design Technique, Object Diagram Compiler, and the Future of Object-Oriented Technology.
Journal ArticleDOI

A spiral model of software development and enhancement

Barry Boehm
- 01 May 1988 - 
TL;DR: An outline is given of the process steps involved in the spiral model, an evolving risk-driven approach that provides a framework for guiding the software process and its application to a software project is shown.
Book

The knowledge level

Allen Newell
TL;DR: A theory of the nature of knowledge is proposed, namely, that there is another computer system level immediately above the symbol (or program) level and knowledge itself is the processing medium at this level and the principle of rationality plays a central role.
Book

Principles of database and knowledge-base systems

TL;DR: This book goes into the details of database conception and use, it tells you everything on relational databases from theory to the actual used algorithms.