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ACL
1997

String Transformation Learning

13 years 11 months ago
String Transformation Learning
String transformation systems have been introduced in (Brill, 1995) and have several applications in natural language processing. In this work we consider the computational problem of automatically learning from a given corpus the set of transformations presenting the best evidence. We introduce an original data structure and efficient algorithms that learn some families of transformations that are relevant for part-of-speech tagging and phonological rule systems. We also show that the same learning problem becomes NP-hard in cases of an unbounded use of don't care symbols in a transformation.
Giorgio Satta, John C. Henderson
Added 01 Nov 2010
Updated 01 Nov 2010
Type Conference
Year 1997
Where ACL
Authors Giorgio Satta, John C. Henderson
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