Title :
A Family of Similarity Measures Between Two Strings
Author :
Findler, Nicholas V. ; Leeuwen, Jan Van
Author_Institution :
Department of Computer Science, State University of New York at Buffalo, Amherst, NY 14226.
Abstract :
We present a class of similarity measures for quantitatively comparing two strings, that is, two linearly ordered sets of elements. The strings can be of different lengths, the elements come from a single alphabet, and an element may appear any number of times. The limiting values of each measure are 0, when two completely different strings are compared, and 1, when the two strings are identical. Applications of similarity measures are numerous in nonnumerical computations, such as in heuristic search processes in associative networks, in pattern recognition and classification, in game playing programs, and in music and text analysis. We offer a number of feasible measures from among which some are discarded on plausibility grounds. One can select the measure most adequate for one´s needs on the basis of a few characteristic examples of strings compared and by considering the specific requirements of the application at hand.
Keywords :
Application software; Computer networks; Computer science; Pattern recognition; Solids; Text analysis; Classification problems; pattern recognition; search processes; similarity measures between strings; substrings;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.1979.4766885