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== Applications == WordNet has been used for a number of purposes in information systems, including [[word-sense disambiguation]], [[information retrieval]], [[Document classification|automatic text classification]], [[automatic summarization|automatic text summarization]], [[machine translation]] and even automatic crossword puzzle generation. A common use of WordNet is to determine the [[semantic similarity|similarity]] between words. Various algorithms have been proposed, including measuring the distance among words and [[Synset|synsets]] in WordNet's graph structure, such as by counting the number of edges among synsets. The intuition is that the closer two words or synsets are, the closer their meaning. A number of WordNet-based word similarity algorithms are implemented in a [[Perl]] package called WordNet::Similarity,<ref>{{cite web|url=http://www.d.umn.edu/~tpederse/similarity.html |title=Ted Pedersen - WordNet::Similarity |publisher=D.umn.edu |date=2008-06-16 |access-date=2014-03-11}}</ref> and in a [[Python (programming language)|Python]] package called [[NLTK]].<ref>[https://likegeeks.com/nlp-tutorial-using-python-nltk NLP using Python NLTK]/</ref> Other more sophisticated WordNet-based similarity techniques include ADW,<ref>M. T. Pilehvar, D. Jurgens and R. Navigli. [http://wwwusers.di.uniroma1.it/~navigli/pubs/ACL_2013_Pilehvar_Jurgens_Navigli.pdf Align, Disambiguate and Walk: A Unified Approach for Measuring Semantic Similarity.]. Proc. of the 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013), Sofia, Bulgaria, August 4β9, 2013, pp. 1341-1351.</ref> whose implementation is available in [[Java (programming language)|Java]]. WordNet can also be used to inter-link other vocabularies.<ref>{{cite journal |vauthors=Ballatore A, etal |volume=20|issue=2| arxiv=1404.5372| journal=Annals of GIS |title=Linking geographic vocabularies through WordNet |date=2014|pages=73β84|doi=10.1080/19475683.2014.904440|bibcode=2014AnGIS..20...73B|s2cid=9246582}}</ref>
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