Generalizing predicates with string arguments

Date
2006-06
Authors
Cicekli, I.
Cicekli, N. K.
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Source Title
Applied Intelligence: the international journal of artificial intelligence, neural networks, and complex problem-solving technologies
Print ISSN
0924-669X
Electronic ISSN
Publisher
Springer New York LLC
Volume
25
Issue
Pages
23 - 36
Language
English
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Abstract

The least general generalization (LGG) of strings may cause an over-generalization in the generalization process of the clauses of predicates with string arguments. We propose a specific generalization (SG) for strings to reduce over-generalization. SGs of strings are used in the generalization of a set of strings representing the arguments of a set of positive examples of a predicate with string arguments. In order to create a SG of two strings, first, a unique match sequence between these strings is found. A unique match sequence of two strings consists of similarities and differences to represent similar parts and differing parts between those strings. The differences in the unique match sequence are replaced to create a SG of those strings. In the generalization process, a coverage algorithm based on SGs of strings or learning heuristics based on match sequences are used. © Springer Science + Business Media, LLC 2006.

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