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A learning algorithm for top-down XML transformations

2010
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Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems of data - PODS '10
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A generalization from string to trees and from languages to translations is given of the classical result that any regular language can be learned from examples: it is shown that for any deterministic top-down tree transformation there exists a sample set of polynomial size (with respect to the minimal transducer) which allows to infer the translation. Until now, only for string transducers and for simple relabeling tree transducers, similar results had been known. Learning of deterministic

doi:10.1145/1807085.1807122
dblp:conf/pods/LemayMN10
fatcat:fylbbdxjzbgm7npfnvsw326kja