Affiliations: [a] Department of Chemistry, Memorial University of Newfoundland, NL, Canada | [b] Department of Physics and Physical Oceanography, Memorial University of Newfoundland, NL, Canada | [c] Eötvös Loránd University of Budapest, Budapest, Hungary | [d] Department of Chemistry and Biochemistry, Babes-Bolyai University, Cluj-Napoca, Romania
Correspondence:
[*]
Corresponding author: Paul G. Mezey, Department of Chemistry, Memorial University of Newfoundland, 283 Prince Philip Drive, St. John's, NL, A1B 3X7, Canada. Tel.: +1 709 737 8768; Fax: +1 709 737 3702; E-mail:paul.mezey@gmail.com
Abstract: Using only numerical differences of descriptors of entries in databases and
the subsequent generation of iterated difference sequences, a simple
similarity characterization and efficient approximate similarity measures
can be obtained for the database entries, and for some families of
functional relations among databank entries, information on the dominant
power dependence of such functions interrelating the database entries can be
obtained, without the involvement of any fitting algorithm. After the
dominant power dependence has been determined by this simple approach, and
if more precise functional relations are needed, this knowledge allows one
to choose better trial functions fulfilling this constraint, instead of a
``trial and error'' approach more commonly used for the determination of
unknown functions describing the relations among the database entries with
respect to the given property.
Keywords: Data mining, similarity searches in databanks, difference sequences, factorial level similarity, dominant power determination by difference sequence methods
