Ontologies in Support of Data-Mining Based on Associated Rules: a Case Study in a Medical Diagnosis Company
نویسندگان
چکیده
A well-known alternative to identify hidden standards is the use of data mining techniques. In order to obtain more efficiency in data mining, ontologies have been used to improve the representation in specialized knowledge domains. Here, we apply ontologies in a dataset of a diagnostic medicine company, which concerns to viral human hepatitis, with the aim of obtaining the best correlations between the laboratory tests prescribed by physicians and the real occurrences of diseases. Our preliminary findings show that the use of ontologies provides reduction in the number of attributes in the pre-processing phase, then improving the performance of data mining process as a whole.
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