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Morphology Induction from Term Clusters (2005)
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| Venue: | PROCEEDINGS OF THE 9TH CONFERENCE ON COMPUTATIONAL NATURAL LANGUAGE LEARNING (CONLL) |
| Citations: | 25 - 0 self |
BibTeX
@MISC{Freitag05morphologyinduction,
author = {Dayne Freitag},
title = {Morphology Induction from Term Clusters},
year = {2005}
}
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Abstract
We address the problem of learning a morphological automaton directly from a monolingual text corpus without recourse to additional resources. Like previous work in this area, our approach exploits orthographic regularities in a search for possible morphological segmentation points. Instead of affixes, however, we search for affix transformation rules that express correspondences between term clusters induced from the data. This focuses the system on substrings having syntactic function, and yields cluster-to-cluster transformation rules which enable the system to process unknown morphological forms of known words accurately. A stem-
Keyphrases
term cluster morphology induction possible morphological segmentation point yield cluster-to-cluster transformation rule syntactic function known word orthographic regularity additional resource unknown morphological form affix transformation rule monolingual text corpus morphological automaton previous work
