• Publications
  • Influence
Foundation and application of knowledge base verification
Anomalies such as redundant, contradictory, and deficient knowledge in a knowledge base are symptoms of probable errors. Detecting anomalies is a well‐established method for verifying knowledge‐basedExpand
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Ontology Reconciliation
Ontologies are being applied very successfully in supporting information and knowledge exchange between people and organisations. However, for many reasons, different people and organisations willExpand
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Agent-based formation of virtual organisations
Virtual organisations (VOs) are composed of a number of individuals, departments or organisations each of which has a range of capabilities and resources at their disposal. These VOs are formed soExpand
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The KRAFT architecture for knowledge fusion and transformation
This paper describes the Knowledge Reuse And Fusion/Transformation (KRAFT) architecture which supports the fusion of knowledge from multiple, distributed, heterogeneous sources. The architecture usesExpand
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Principles and practice in verifying rule-based systems
This paper surveys the verification of expert system knowledge bases by detecting anomalies. Such anomalies are highly indicative of errors in the knowledge base. The paper is in two parts. The firstExpand
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Better Knowledge Management through Knowledge Engineering
The authors believe that current knowledge management practice significantly under-utilizes knowledge engineering technology, despite recent efforts to promote its use. They focus on two knowledgeExpand
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Kraft: An Agent Architecture for Knowledge Fusion
Knowledge fusion refers to the process of locating and extracting knowledge from multiple, heterogeneous on-line sources, and transforming it so that the union of the knowledge can be applied inExpand
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Verifying ontological commitment in knowledge-based systems
Abstract An ontology defines the terminology of a domain of knowledge: the concepts that constitute the domain, and the relationships between those concepts. In order for two or more knowledge-basedExpand
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Asking 'Why' in AI: Explainability of intelligent systems - perspectives and challenges
  • A. Preece
  • Computer Science
  • Intell. Syst. Account. Finance Manag.
  • 1 April 2018
Recent rapid progress in machine learning (ML), particularly so‐called ‘deep learning’, has led to a resurgence in interest in explainability of artificial intelligence (AI) systems, reviving an areaExpand
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Sensor-Mission Assignment in Constrained Environments
When a sensor network is deployed in the field it is typically required to support multiple simultaneous missions, which may start and finish at different times. Schemes that match sensor resourcesExpand
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