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Soft Computing
Published in: Soft Computing 8/2018

15-07-2017 | Foundations

Multiple attribute similarity hypermatching

Authors: Ronald Yager, Fred Petry, Paul Elmore

Published in: Soft Computing | Issue 8/2018

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Abstract

An approach to objects or events similarity is based on the similarity of the data values of the specific attributes. Similarity is refined by considering importance weights for attributes and also the issues of unusual attribute values where the concept of importance amplification is used to provide soft matching of objects or events We then introduce extensions to hypermatching where certain combinations of attributes are relevant. This is approached by modeling how to represent commonly occurring attribute data values whose co-occurrence is uncommon. Certainly not all attribute combinations are typically of the same interest. What can be expected is that for a particular context or application, some subset of the attributes is being focused upon. As an application, we illustrate the importance of considering combinations of attribute values in assessing evidence in geospatial profiling.
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Footnotes
1
This is based on comments from one of the reviewers.
 
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Metadata
Title
Multiple attribute similarity hypermatching
Authors
Ronald Yager
Fred Petry
Paul Elmore
Publication date
15-07-2017
Publisher
Springer Berlin Heidelberg
Published in
Soft Computing / Issue 8/2018
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-017-2721-5

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