Enriched property ontology for knowledge systems : a thesis presented in partial fulfilment of the requirements for the degree of Master of Information Systems in Information Systems, Massey University, Palmerston North, New Zealand
| dc.contributor.author | Minchin, Robert | |
| dc.date.accessioned | 2017-11-08T21:56:16Z | |
| dc.date.available | 2017-11-08T21:56:16Z | |
| dc.date.issued | 2006 | |
| dc.description.abstract | "It is obvious that every individual thing or event has an indefinite number of properties or attributes observable in it and might therefore be considered as belonging to an indefinite number of different classes of things" [Venn 1876]. The world in which we try to mimic in Knowledge Based (KB) Systems is essentially extremely complex especially when we attempt to develop systems that cover a domain of discourse with an almost infinite number of possible properties. Thus if we are to develop such systems how do we know what properties we wish to extract to make a decision and how do we ensure the value of our findings are the most relevant in our decision making. Equally how do we have tractable computations, considering the potential computation complexity of systems required for decision making within a very large domain. In this thesis we consider this problem in terms of medical decision making. Medical KB systems have the potential to be very useful aids for diagnosis, medical guidance and patient data monitoring. For example in a diagnostic process in certain scenarios patients may provide various potential symptoms of a disease and have defining characteristics. Although considerable information could be obtained, there may be difficulty in correlating a patient's data to known diseases in an economic and efficient manner. This would occur where a practitioner lacks a specific specialised knowledge. Considering the vastness of knowledge in the domain of medicine this could occur frequently. For example a Physician with considerable experience in a specialised domain such as breast cancer may easily be able to diagnose patients and decide on the value of appropriate symptoms given an abstraction process however an inexperienced Physician or Generalist may not have this facility.[FROM INTRODUCTION] | en_US |
| dc.identifier.uri | http://hdl.handle.net/10179/12332 | |
| dc.language.iso | en | en_US |
| dc.publisher | Massey University | en_US |
| dc.rights | The Author | en_US |
| dc.subject | Expert systems (Computer science) | en_US |
| dc.subject | Medical informatics | en_US |
| dc.title | Enriched property ontology for knowledge systems : a thesis presented in partial fulfilment of the requirements for the degree of Master of Information Systems in Information Systems, Massey University, Palmerston North, New Zealand | en_US |
| dc.type | Thesis | en_US |
| massey.contributor.author | Minchin, Robert | |
| thesis.degree.discipline | Information Systems | en_US |
| thesis.degree.grantor | Massey University | en_US |
| thesis.degree.level | Masters | en_US |
| thesis.degree.name | Master of Information Systems (M. I. S.) | en_US |
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