Abstract
Wordnets are rich lexico-semantic resources. Linked wordnets are extensions
of wordnets, which link similar concepts in wordnets of different languages.
Such resources are extremely useful in many Natural Language Processing (NLP)
applications, primarily those based on knowledge-based approaches. In such
approaches, these resources are considered as gold standard/oracle. Thus, it is
crucial that these resources hold correct information. Thereby, they are
created by human experts. However, manual maintenance of such resources is a
tedious and costly affair. Thus techniques that can aid the experts are
desirable. In this paper, we propose an approach to link wordnets. Given a
synset of the source language, the approach returns a ranked list of potential
candidate synsets in the target language from which the human expert can choose
the correct one(s). Our technique is able to retrieve a winner synset in the
top 10 ranked list for 60% of all synsets and 70% of noun synsets.