Paper: Morphology Induction From Term Clusters

ACL ID W05-0617
Title Morphology Induction From Term Clusters
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2005
Authors

We address the problem of learning a morphological automaton directly from a monolingual text corpus without re- course to additional resources. Like pre- vious work in this area, our approach ex- ploits 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 hav- ing syntactic function, and yields cluster- to-cluster transformation rules which en- able the system to process unknown mor- phological forms of known words accu- rately. A stem-weighting algorithm based on Hubs and Authorities is used to clar- ify ambiguous segmentation points. We evaluate our approach using the CELEX d...