Abstract
In a multilingual country such as India, machine translation and crosslingual search are highly relevant problems. The WordNets, as crucial linguistic resources, play the most dominant role in the field of text processing and applications, such as machine learning, machine translation, information extraction, information retrieval, and natural language understanding systems. Therefore, no meaningful research in these areas can be complete without their help. This paper reports the categorization work of synsets of the Hindi WordNet (version 1.2), the challenges that were faced while doing the work, and solutions obtained for them thereafter. There are a number of concepts common to most of the languages, and linking these concepts with each other can provide an indispensable resource for Natural Language Processing and Language technology. The WordNet for Hindi language is created using the ab initio method while all the other Indian language WordNets are being created using the Hindi WordNet through expansion approach. The Hindi WordNet forms the foundation for the other Indian language WordNets as they are based on it and are being linked to it.
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