Knowledge Engineering for Practical Applications

Maurice Mulvenna, Peng Ye, Michael McTear, Maureen Murphy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A method is necessary to develop any piece of complex software. There are many methodologies which span the spectrum of software development. These range from specialised methods which accommodate real-time issues, to methods which embrace object-oriented systems. In addition, for Knowledge Based System (KBS) development, the pre-eminent methodology is KADS1.The argument advanced in this paper is that, when building KBS for practical applications, the method used for analysis, design and development may not necessarily be a specialised KBS method. There are reasons for this decision. Firstly, the new generation of KBS form only a part of an IT solution. That is, the KBS may not be the dominant IT component. Therefore any method must encompass the whole IT solution. Secondly, as will be shown by the case studies outlined in this paper, the term “KBS” now encompasses many disparate AI technologies. Specialised KBS methodologies may be restrictive for the development of systems utilising Case Based Reasoning (CBR), Constraint Logic Programming (CLP), Fuzzy Systems, Adaptive Neural Networks, Object-Oriented Systems (OOS), or their combinations.
LanguageEnglish
Title of host publicationUnknown Host Publication
Number of pages6
Publication statusAccepted/In press - 1 Aug 1994
EventSecond European Congress on Intelligent Techniques and Soft Computing - Aachen, Germany
Duration: 1 Aug 1994 → …

Conference

ConferenceSecond European Congress on Intelligent Techniques and Soft Computing
Period1/08/94 → …

Fingerprint

Knowledge engineering
Knowledge based systems
Case based reasoning
Logic programming
Fuzzy systems
Software engineering
Neural networks

Keywords

  • Knowledge Engineering

Cite this

Mulvenna, M., Ye, P., McTear, M., & Murphy, M. (Accepted/In press). Knowledge Engineering for Practical Applications. In Unknown Host Publication
Mulvenna, Maurice ; Ye, Peng ; McTear, Michael ; Murphy, Maureen. / Knowledge Engineering for Practical Applications. Unknown Host Publication. 1994.
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Mulvenna, M, Ye, P, McTear, M & Murphy, M 1994, Knowledge Engineering for Practical Applications. in Unknown Host Publication. Second European Congress on Intelligent Techniques and Soft Computing, 1/08/94.

Knowledge Engineering for Practical Applications. / Mulvenna, Maurice; Ye, Peng; McTear, Michael; Murphy, Maureen.

Unknown Host Publication. 1994.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AU - Mulvenna, Maurice

AU - Ye, Peng

AU - McTear, Michael

AU - Murphy, Maureen

PY - 1994/8/1

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N2 - A method is necessary to develop any piece of complex software. There are many methodologies which span the spectrum of software development. These range from specialised methods which accommodate real-time issues, to methods which embrace object-oriented systems. In addition, for Knowledge Based System (KBS) development, the pre-eminent methodology is KADS1.The argument advanced in this paper is that, when building KBS for practical applications, the method used for analysis, design and development may not necessarily be a specialised KBS method. There are reasons for this decision. Firstly, the new generation of KBS form only a part of an IT solution. That is, the KBS may not be the dominant IT component. Therefore any method must encompass the whole IT solution. Secondly, as will be shown by the case studies outlined in this paper, the term “KBS” now encompasses many disparate AI technologies. Specialised KBS methodologies may be restrictive for the development of systems utilising Case Based Reasoning (CBR), Constraint Logic Programming (CLP), Fuzzy Systems, Adaptive Neural Networks, Object-Oriented Systems (OOS), or their combinations.

AB - A method is necessary to develop any piece of complex software. There are many methodologies which span the spectrum of software development. These range from specialised methods which accommodate real-time issues, to methods which embrace object-oriented systems. In addition, for Knowledge Based System (KBS) development, the pre-eminent methodology is KADS1.The argument advanced in this paper is that, when building KBS for practical applications, the method used for analysis, design and development may not necessarily be a specialised KBS method. There are reasons for this decision. Firstly, the new generation of KBS form only a part of an IT solution. That is, the KBS may not be the dominant IT component. Therefore any method must encompass the whole IT solution. Secondly, as will be shown by the case studies outlined in this paper, the term “KBS” now encompasses many disparate AI technologies. Specialised KBS methodologies may be restrictive for the development of systems utilising Case Based Reasoning (CBR), Constraint Logic Programming (CLP), Fuzzy Systems, Adaptive Neural Networks, Object-Oriented Systems (OOS), or their combinations.

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BT - Unknown Host Publication

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Mulvenna M, Ye P, McTear M, Murphy M. Knowledge Engineering for Practical Applications. In Unknown Host Publication. 1994