Mooney, R. J., and M. E. Califf. 1996. Learning the past tense of english verbs using inductive logic programming. In S. Wermter, E. Riloff, and G. Scheler (Eds.), Symbolic, Connectionist, and Statistical Approaches to Learning for Natural Language Processing. Springer Verlag.  Home/Search Document Details and Download
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Machine Learning and Natural Language Processing - Marquez (2000) (1 citation) (Correct)
.... of ILP to NLP can be found in [151] Particular works include applications to grammatical inference [247, 248] automatic induction of natural language interfaces for querying data bases [249, 222] information extraction tasks [216, 217, 29, 79, 80, 81, 30, 215] acquisition of verbal properties [153], text categorization [49, 50, 53, 213] and generation of natural language [176] 2.3 Subsymbolic Machine Learning Approaches 2.3.1 Neural Networks In their relation to NLP, neural networks [94] have been used basically to address low level problems, such as OCR [204] speech recognition and ....
....NLP tasks, such those related with machine translation, spelling correction, etc. DTs ME IBL TBL NB Acquisition of verbal properties [221, 209] General machine translation [10] 100] Spelling correction [133] 86, 88, 89] DLs ILP NNs Clust GAs LSM LogL Acquisition of verbal properties [152, 153, 29] [209] 209, 135] General machine translation [235] Spelling correction [241, 208] 116] 89] Generation [176] Table 5: References corresponding to Machine Translation and other NLP tasks 14 3 Word Sense Disambiguation: A Case Study in Supervised Machine Learning The present section is ....
R. J. Mooney and M. E. Califf. Learning the Past Tense of English Verbs Using Inductive Logic Programming. In E. Riloff S. Wermter and G. Scheler, editors, Connectionist, Statistical an Symbolic Approaches to Learning for Natural Language Processing, Lecture Notes in Artificial Intelligence, 1040. Springer, 1996.
Induction of Recursive Transfer Rules - Boström (1 citation) (Correct)
.... it tries to identify non recursive correspondences between the source and target QLFs, second, it generates a set of as general clauses as possible for each example and third, it specialises the clauses so that for each source QLF exactly one target QLF can be generated (cf. output completeness [9]) In the previous work, the system relied on elaborated, hand coded heuristics for the first step. In this work we assume no such heuristics, but instead assume that the non recursive transfer rules are known, and hence the task is to induce the recursive rules (initial work on inducing ....
Mooney R. J. and Califf M. E., "Learning the Past Tense of English Verbs Using Inductive Logic Programming", in Wermter S., Riloff E. and Scheler G. (eds.), Symbolic, Connectionist and Statistical Approaches to Learning for Natural Language Pr ocessing, Springer-Verlag (1996) 370--384
The Segmentation Problem in Morphology Learning - Manning (1998) Self-citation (Mooney) (Correct)
.... 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 ....
Mooney, R. J., and M. E. Califf. 1996. Learning the past tense of english verbs using inductive logic programming. In S. Wermter, E. Riloff, and G. Scheler (Eds.), Symbolic, Connectionist, and Statistical Approaches to Learning for Natural Language Processing. Springer Verlag.
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