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When is a String Like a String? L. Allison, C. S. Wallace and C. N. Yee.

Summary: When is a String Like a String?
L. Allison, C. S. Wallace and C. N. Yee.
Department of Computer Science,
Monash University,
Australia 3168.
UUCP: xxx@.cs.monash.edu.au xxx=[lloyd, csw, cyee]
Supported by Australian Research Council grant A48830856
version: 15 Dec 1989
Presented at the International Symposium on Artificial Intelligence and Mathematics, Ft. Lauderdale,
Florida, January 3-5 1990.
Abstract. The question of whether or not two strings are related and, if so, of how they are related and the
problem of finding a good model of string relation are treated as inductive inference problems. A method
of inductive inference known as minimum message length encoding is applied to them. It allows the
posterior odds­ratio of two theories or hypotheses to be computed. New string comparison algorithms and
methods are derived and existing algorithms are placed in a unifying framework. The connection between
string comparison algorithms and models of relation is made explicit. The posterior probability of two
strings' being related can be calculated, giving a test of significance. The methods are relevant to DNA and
to other biological macro­molecules.
Keywords: string, inductive inference, minimum message length, pattern matching, DNA, macro­


Source: Allison, Lloyd - Caulfield School of Information Technology, Monash University


Collections: Computer Technologies and Information Sciences