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Usual operations with symbolic data under normal symbolic form
Author(s) -
Csernel Marc,
De Carvalho F. A. T.
Publication year - 1999
Publication title -
applied stochastic models in business and industry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.413
H-Index - 40
eISSN - 1526-4025
pISSN - 1524-1904
DOI - 10.1002/(sici)1526-4025(199910/12)15:4<241::aid-asmb390>3.0.co;2-z
Subject(s) - computer science , the symbolic , symbolic data analysis , symbolic trajectory evaluation , focus (optics) , symbolic computation , theoretical computer science , domain (mathematical analysis) , space (punctuation) , algorithm , mathematics , model checking , psychology , mathematical analysis , physics , optics , psychoanalysis , operating system
Rather than representing data as points within the description space, symbolic objects represent them as hyper‐rectangles, in order to take into account some variability within the description. They also make it possible to add some domain knowledge represented by rules which reduce the description space. Unfortunately, this supplementary knowledge usually induces a combinatorial growing of the possible calculus time. In a previous paper we presented a method leading to a decomposition of symbolic objects into a normal symbolic form (NSF) which allows an easier calculation, however great the number of rules may be. In this paper, after recalling what symbolic objects and the NSF are, we focus on the different kinds of operation that can be used when dealing with symbolic objects. We show that the different operations are stable or quasi‐stable regarding the NSF. We then see that by applying NSF to distance computation we obtained, in our first trial, a reduction of over 90 per cent in our computational time. Copyright © 1999 John Wiley & Sons, Ltd.