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Comparing Apples and Orange Cottages

Authors:
Julia M. Taylor
Victor Raskin

Keywords: comparison; classification; hierarchy; propert;, similarity; ontology; concept.

Abstract:
This paper deals with the rules of good classification and comparison, as well as matching the representation of the results with what has actually been accomplished. The emphasis in machine learning classifications, as well as, sometimes, outside of that paradigm, is almost exclusively on the precision of separating classes from each other, and hardly any effort is made to assess the nature of the classes with regard to their grain size. This results in a considerable disparity between the claimed results and what is really demonstrated, leading in turn to crude solutions to issues and poorly functioning applications. We propose an ontological solution, following the explicit tracing of a conceptual hierarchy underlying the classes. This approach may lead to a variety of solutions that can be compared after classification and similarity studies mature enough to face the issue.

Pages: 96 to 102

Copyright: Copyright (c) IARIA, 2015

Publication date: March 22, 2015

Published in: conference

ISSN: 2308-4197

ISBN: 978-1-61208-390-2

Location: Nice, France

Dates: from March 22, 2015 to March 27, 2015