All Words Unsupervised Semantic Category Labeling for Hindi
Siva Reddy, Abhilash Inumella, Rajeev Sangal, Soma Paul · Recent Advances in Natural Language Processing · 2009
In the task of semantic category labeling, given a text, every word in it has to be assigned a semantic category. Our language of interest is Hindi. We use the ontological categories defined in Hindi Wordnet as semantic category inventories. In this paper we present two unsupervised approaches namely Flat Semantic Category Labeler (FSCL) and Hierarchical Semantic Category Labeler (HSCL ). The former method treats semantic categories as a flat list, whereas the latter one exploits the hierarchy among the semantic categories in a top down manner. Further our methods use simple probabilistic models, using which the category labeling becomes a simple table look up with little extra computation and thus opening the possibility of it’s use in real-time interactive systems.