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Title: A polynomial time computable metric between point sets
Authors: Ramon, Jan ×
Bruynooghe, Maurice #
Issue Date: Jul-2001
Publisher: Springer-verlag
Series Title: Acta informatica vol:37 issue:10 pages:765-780
Abstract: Measuring the similarity or distance between sets of points in a metric space is an important problem in machine learning and has also applications in other disciplines e.g. in computational geometry, philosophy of science, methods for updating or changing theories,... . Recently Eiter and Mannila have proposed a new measure which is computable in polynomial time. However, it is not a distance function in the mathematical sense because it does not satisfy the triangle inequality. We introduce a new measure which is a metric while being computable in polynomial time. We also present a variant which computes a normalised metric and a variant which can associate different weights with the points in the set.
ISSN: 0001-5903
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Informatics Section
× corresponding author
# (joint) last author

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