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A methodology forthe modeling of large data sets is described which results in rule sets having minimal inter-rule interactions, and being simply maintained. An algorithm for developing such rule sets automatically is described and its efficacy shown with standard test data sets. Comparative studies of manual and automatic modeling of a data set of some(More)
Knowledge engineering, obtaining knowledge from experts and incorporating it into expert systems is difficult and time consuming. We suggest that these difficulties arise because experts never report on how they reach a decision, rather they justify why the decision is correct. These justifications vary markedly with the context in which they are required,(More)
Provision of a comprehensive interpretative service is an important challenge facing chemical pathologists. Attempts to automate report interpretation using expert systems have been limited in the past by the difficulties of rule base maintenance. We have applied a novel knowledge acquisition technique, ripple down rules, in the development of PEIRS(More)
This paper suggests that a distinction between knowledge acquisition methods should be made. On the one hand there are methods which aim to help the expert and knowledge engineer analyse what knowledge is involved in solving a particular type of problem and how this problem solving is carried out. These methods are concerned with classifying the different(More)
Knowledge-based systems (KBS) are not necessarily based on well-defined ontologies. In particular it is possible to build KBS for classification problems, where there is little constraint on how classes are organised and a class is expressed by the expert as a free text conclusion to a rule. This paper investigates how relations between such 'classes' may(More)
The major focus of recent knowledge acquisition research has been on problem-solving methods (PSM). This paper present results where a PSM developed for classification has been extended to handle a configuration or parametric design task, designing ion chromatography methods in analytical chemistry. Surprisingly good results have been obtained seemingly(More)
Link prediction is a key technique in many applications in social networks, where potential links between entities need to be predicted. Conventional link prediction techniques deal with either homogeneous entities, e.g., people to people, item to item links, or non-reciprocal relationships, e.g., people to item links. However, a challenging problem in link(More)
Ripple-Down Rules (RDR) is an approach to building knowledge-based systems (KBS) incrementally, while the KBS is in routine use. Domain experts build rules as a minor extension to their normal duties, and are able to keep refining rules as KBS requirements evolve. Commercial RDR systems are now used routinely in some Chemical Pathology laboratories to(More)