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CSI Transactions on ICT
Article . 2013 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
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Development of Punjabi WordNet

Authors: Parteek Kumar; Ashish Narang; Rajendra Kumar Sharma;

Development of Punjabi WordNet

Abstract

Natural language processing (NLP) tasks such as word sense disambiguation, machine translation (MT) and part-of-speech tagging etc. require large scale lexical resources. These lexical resources have already been developed for digitally advanced languages, such as English, but yet to be developed for widely spoken but digitally young languages, such as Punjabi. WordNet is one such lexical resource that can be used for variety of NLP tasks ranging from digital dictionary to automated MT. The basic building block of WordNet is synset, a word sense with which one or more synonymous words are associated. Each synset in WordNet is linked to other synsets using lexical and semantic relations. Lexical relations are between word forms, whereas semantic relations exist between two whole synsets. This paper presents lexical and semantic relations of Punjabi WordNet, including synonymy, hypernymy/hyponymy, meronymy/holonomy, entailment and troponymy etc. It also illustrates the process of creation of Punjabi synsets from Hindi synsets, design of synsets and semantic databases for implementation of semantic relations for Punjabi WordNet.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Top 10%
Top 10%
Average
bronze