Journal ArticleDOI
Applying systems analysis techniques to knowledge engineering
Gail Swaffield,Brian Knight +1 more
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TLDR
The methods proposed lay emphasis on the definition of limited data sets at the boundary of the explicit knowledge base and the identification of status attributes to model the control of activation of ‘processes’ within the knowledge base.Abstract:
This paper deals with the issue of knowledge elicitation for expert systems. Specifically, it looks at the requirements of the knowledge elicitation process and the suitability of structured methods from systems analysis to carry out part of the elicitation task. The techniques of data flow analysis, entity-relationship analysis and entity-life cycle analysis are used to structure the data associated with the expert task. The methods proposed lay emphasis on the definition of limited data sets at the boundary of the explicit knowledge base and the identification of status attributes to model the control of activation of ‘processes’ within the knowledge base. Attention is also paid to the relationship between the resulting logical model, and two popular methods of knowledge representation, namely, Production Systems and Frames.read more
Citations
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Journal ArticleDOI
Using anthropological interview strategies to enhance knowledge acquisition
TL;DR: Examples of the questions used to perform each knowledge elicitation task are presented along with a description of the controls used to assure accuracy in developing the related knowledge base.
Knowledge Elicitation for Design Task Sequencing Knowledge
TL;DR: An approach is used that combines two knowledge elicitation techniques: one direct, to directly request the design steps and their sequence, and one indirect, to refine this knowledge by obtaining steps and sequences that may be implicit.
Journal ArticleDOI
An Approach to Effective Job Placement in an Organization: A Case Study
TL;DR: This study suggests an expert system leading to a running system as a means for effective job placement, especially focusing on the main components of the expert system such as structure of rule base, inference engine, and user interface.
Journal ArticleDOI
An expert system for predicting gas demand: a case study
TL;DR: This paper is a case study of an expert system built by the Operational Research Section at British Gas South Eastern, to predict the demand for gas for the next day, with particular emphasis on the knowledge acquisition techniques used.
Journal ArticleDOI
Exploring the relationship between system development life cycle and knowledge accumulation in Taiwan's IT industry
Wen-Hsiang Lai,Hsin-Cheng Tsen +1 more
TL;DR: This study investigates how the effectiveness of SDLC (ESDLC) correlates with KI, OKA, and EKA, and indicates that EKA and OKA have obvious mutual influences, and that both show significant impact on ESDLC.
References
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Book
The entity-relationship model: toward a unified view of data
TL;DR: A data model, called the entity-relationship model, is proposed that incorporates some of the important semantic information about the real world and can be used as a basis for unification of different views of data: the network model, the relational model, and the entity set model.
Proceedings ArticleDOI
The entity-relationship model: toward a unified view of data
TL;DR: A data model, called the entity-relationship model, which incorporates the semantic information in the real world is proposed, and a special diagramatic technique is introduced for exhibiting entities and relationships.
Proceedings ArticleDOI
Another look at data
TL;DR: This paper sketches a theory of data which may serve to clarify questions about data, based on a number of old ideas which may, as a result, seem obvious.
Book ChapterDOI
Knowledge Elicitation Involving Teachback Interviewing
Leslie Johnson,Nancy E. Johnson +1 more
TL;DR: The authors' knowledge elicitation technique has at its center a program of semi-structured interviews by a methodology based on conversation theory (Pask, 1974).
Journal ArticleDOI
Experiments on the Mechanization of Game-learning 2—Rule-Based Learning and the Human Window
TL;DR: The first successful learning programs were developed in the 1950s and belonged to a general category which was at that time commonly known as 'hill-climbing', which embraces classical adaptive control, along with many studies of machine learning in games and game-like situations.
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