Sauer, Christian (2016) Knowledge elicitation and formalisation for context and explanation-aware computing with case-based recommender systems. Doctoral thesis, University of West London.

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Abstract

Case-based reasoning (CBR), as one of the problem solving paradigms in the field of Artificial Intelligence (AI), is an approach to the re-use of experience to solve problem. The aim of this research was to identify and evaluate existing and new approaches to elicit and formalise knowledge for context-aware systems as well as systems that are able to perform explanation-aware computing.
The research was centred on systems that employ the specific AI approach of CBR. The research identified positive and negative effects of knowledge formalisation as well as synergies of knowledge formalisation for context-awareness and explanation-aware computing. The research focused on a set of specific knowledge sources such as sensors, human experts, online sources such as web communities and social media as well as a combination of these sources. A set of knowledge formalisation approaches was evaluated during the implementation of six prototype systems, representing a series of product- and work-flow recommender systems. Example domains for the systems developed include CBR-based recommendation in audio mastering, gold ore refinement and travel medicine. Test data gathered from real-world use of the prototypes formed the basis for a quantitative and qualitative analysis to establish the performance and quality of the knowledge formalisation approaches used within the prototypes development. The outcome of this research work consists of new approaches to knowledge elicitation and formalisation for expert work-flow recommender systems, new approaches to context- and explanatory-knowledge formalisation in combination with software engineering techniques, new approaches to knowledge extraction and formalisation from web sources and contributions to the further development of the myCBR 3 software, an open source software for the rapid prototyping of CBR systems.

Item Type:	Thesis (Doctoral)
Subjects:	Computing
Depositing User:	Christian Sauer
Date Deposited:	27 May 2016 15:17
Last Modified:	28 Aug 2021 07:20
URI:	https://repository.uwl.ac.uk/id/eprint/2226

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