Multiple attribute similarity hypermatching
- 186 Downloads
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.
KeywordsAttribute importance Combination of attributes Amplification Soft matching Similarity
Elmore and Petry were supported in part by the Naval Research Laboratory’s Base Program, Program Element No. 0602435 N. Ronald Yager has been in part supported by ONR Grant Award Number N00014-13-1-0626.
Compliance with ethical standards
Conflict of interest
Authors Yager, Elmore and Petry declare they have no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
- Brown A, Smith A, Elmhurst O (2002) The combined use of pollen and soil analyses in a search and subsequent murder investigation. J Forensic Sci 47:614–618Google Scholar
- Canter D, Youngs D (2008) Principles of geographical offender profiling. Ashgate Publishing, FarnhamGoogle Scholar
- Castillo E (1988) Extreme value theory in engineering. Academic Press, San Diego, CAGoogle Scholar
- Nwosu K, Thurasiingham B, Berra B (2011) Multi-media database systems: design and implementation. Kluwer, NorwellGoogle Scholar
- Rossmo K (2000) Geographical profiling. CRC Press, Boca RatonGoogle Scholar
- Tung A, Zhang R, Koudas N, Ooi B (2006) Similarity search: a matching based approach. In: Proceedings of very large database conference, pp 631–642Google Scholar
- Witten I, Frank E, Hall M (2011) Data mining: practical machine learning tools and techniques, 3rd edn. Morgan Kaufmann, San FranciscoGoogle Scholar