Probabilistic Description, Modeling and Similarity-Ranking of Mineral Deposit Zones


The project applies two formal mathematical constructs to the similarity ranking of descriptions of mineral deposit zones. In so doing, the project will assist metallurgists to cost-effectively identify the most appropriate metallurgical processes for the extraction of metals from different mineral deposit zones. The two mathematical constructs to be used are those of “prior probability”, which assists with the incorporation of knowledge which may be regarded as “common sense” to an expert (eg: the frequency and level of occurrence of nickel in granite), and “Aristotelian class definitions”, which greatly assist in applying logical reasoning to taxonomic terms (eg: rock names) used in the descriptions which are to be compared. The descriptions to be compared are “ontologically controlled”, meaning that they are created using controlled vocabularies and syntax. This is necessary to eliminate the inconsistencies that can arise between descriptions written by different people of the same mineral deposit zone if the vocabulary or syntax they use to describe the zone is not the same, or is the same but has different meanings to the different people. The application will take the form of a software system written in Java and will be deployable in other domains than extractive metallurgy.

Faculty Supervisor:

Dr. Giuseppe Carenini


Jacek Kisynski


GeoReference Online Ltd.


Computer science


Mining and quarrying


University of British Columbia



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