An Agglomerative Hierarchical Clustering Algorithm for Labelling Morphs
Burcu Can, Suresh Manandhar · Recent Advances in Natural Language Processing · 2013
In this paper, we present an agglomerative hierarchical clustering algorithm for labelling morphs. The algorithm aims to capture allomorphs and homophonous morphemes for a deeper analysis of segmentation results of a morphological segmentation system. Most morphological segmentation systems focus only on segmentation rather than labelling morphs according to their roles in words, i.e. inflectional (cases, tenses etc.) vs. derivational. Nevertheless, it is helpful to have a better understanding of the roles of morphs in a word to be able to judge the grammatical function of that word in a sentence; i.e. the syntactic category. We believe that a good morph labelling system can also help partof-speech tagging. The proposed clustering algorithm can capture allomorphs in Turkish successfully. We obtain a recall of 86.34% for Turkish and 84.79% for English.