Output details
11 - Computer Science and Informatics
The University of West London
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Output title
Knowledge Formalisation for hydrometallurgical gold ore processing
Type
E - Conference contribution
DOI
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Name of conference/published proceedings
The Thirty-third SGAI International Conference on Artificial Intelligence
Volume number
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Issue number
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First page of article
n/a
ISSN of proceedings
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Year of publication
2013
URL
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Number of additional authors
2
Additional information
<22> In this paper we created a case-based reasoning application for recommending a pre-treatment process of gold ores. We describe an approach to formalise the necessary knowledge. First, formalising expert knowledge about gold mining situations to enable the retrieval of similar mining contexts and respective process chains, based on prospection data gathered from a potential gold mining site. We demonstrate how similarity knowledge was used to formalise literature knowledge. The evaluation of an initial prototype workflow recommender, AuricAdviser, provides promising results. This paper won the best-refereed application paper award at SG AI-2013.
Interdisciplinary
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Cross-referral requested
-
Research group
None
Citation count
-
Proposed double-weighted
No
Double-weighted statement
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Reserve for a double-weighted output
No
Non-English
No
English abstract
-
