Induction: processes of inference, learning, and discovery
Induction: processes of inference, learning, and discovery
On learning the past tenses of English verbs
Parallel distributed processing: explorations in the microstructure of cognition, vol. 2
Learning the past tense of English verbs using inductive logic programming
Connectionist, Statistical, and Symbolic Approaches to Learning for Natural Language Processing
Learning the past tense of English verbs: the symbolic pattern associator vs. connectionist models
Journal of Artificial Intelligence Research
Induction of first-order decision lists: results on learning the past tense of English verbs
Journal of Artificial Intelligence Research
A naive theory of affixation and an algorithm for extraction
SIGPHON '06 Proceedings of the Eighth Meeting of the ACL Special Interest Group on Computational Phonology and Morphology
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Recently there has been a large literature on various approaches to learning morphology, and the success and cognitive plausibility of different approaches (Rumelhart and McClelland (1986), MacWhinney and Leinbach (1991) arguing for connectionist models, Pinker and Prince (1988), Lachter and Bever (1988), Marcus et al. (1992) arguing against connectionist models, Ling and Marinov (1993), Ling (1994) using ID3/C4.5 decision trees, and Mooney and Califf (1995, 1996) using inductive logic programming/decision lists, among others). However - except for a couple of forays into German - this literature has been exclusively concerned with the learning of the English past tense. This has not worried some. Ling is happy to describe it as "a landmark task". But while the English past tense has some interesting features in its combination of regular rules with semi-productive strong verb patterns, it is in many other respects a very trivial morphological system - reflecting the generally vestigal nature of inflectional morphology within modern English.