We adapt the cognitively-oriented morphology acquisition model proposed in (Chan 2008) to perform morphological analysis, extending its concept of base-derived relationships to allow multi-step derivations and adding features required for robustness on noisy corpora. This results in a rule-based morphological analyzer which attains an F-score of 58.48% in English and 33.61% in German in the Morpho Challenge 2009 Competition 1 evaluation. The learner's performance shows that acquisition models can effectively be used in text-processing tasks traditionally dominated by statistical approaches. © 2010 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Lignos, C., Chan, E., Marcus, M. P., & Yang, C. (2010). A rule-based acquisition model adapted for morphological analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6241 LNCS, pp. 658–665). https://doi.org/10.1007/978-3-642-15754-7_79
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