Abstract
The notion of semantic distance or similarity measurement is closely related to the process of categorization. Any theory of measurement must take into account some real-world results from cognitive science: it is not possible to make a priori judgments about how similar are two random concepts.
The taxonomy presented herein is not unbiased. It clearly implies that the more complex is the semantic distance measure, the more accurate and in line with experience it will be. That is not a particularly comforting result, but the purpose of the taxonomy was to organize the search for accurate semantic distance measures.
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© 1993 Springer-Verlag
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Delugach, H.S. (1993). An exploration into semantic distance. In: Pfeiffer, H.D., Nagle, T.E. (eds) Conceptual Structures: Theory and Implementation. Lecture Notes in Computer Science, vol 754. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-57454-9_9
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DOI: https://doi.org/10.1007/3-540-57454-9_9
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