Simple Morpheme Labelling in Unsupervised Morpheme Analysis
Advances in Multilingual and Multimodal Information Retrieval
ParaMor: minimally supervised induction of paradigm structure and morphological analysis
SigMorPhon '07 Proceedings of Ninth Meeting of the ACL Special Interest Group in Computational Morphology and Phonology
TextGraphs-3 Proceedings of the 3rd Textgraphs Workshop on Graph-Based Algorithms for Natural Language Processing
An analogical learner for morphological analysis
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Overview of Morpho challenge 2008
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
Using unsupervised paradigm acquisition for prefixes
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
MorphoNet: exploring the use of community structure for unsupervised morpheme analysis
CLEF'09 Proceedings of the 10th cross-language evaluation forum conference on Multilingual information access evaluation: text retrieval experiments
Estimating the proximity between languages by their commonality in vocabulary structures
LTC'09 Proceedings of the 4th conference on Human language technology: challenges for computer science and linguistics
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While classical approaches to unsupervised morphology acquisition often rely on metrics based on information theory for identifying morphemes, we describe a novel approach relying on the notion of formal analogy. A formal analogy is a relation between four forms, such as: reader is to doer as reading is to doing. Our assumption is that formal analogies identify pairs of morphologically related words. We first describe an approach which simply identifies all the formal analogies involving words in a lexicon. Despite its promising results, this approach is computationally too expensive. Therefore, we designed a more practical system which learns morphological structures using only a (small) subset of all formal analogies. We tested those two approaches on the five languages used in Morpho Challenge 2009.