NDLI: word2vec or JoBimText?: A Comparison for Lexical Expansion of Hindi Words

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Content Provider	ACM Digital Library
Author	Pawar, Sachin Palshikar, Girish Ramrakhiyani, Nitin
Abstract	Exploration of distributional semantics for NLP tasks in Indian languages has been scarce. This work carries out a comparative analysis of two recent and high performing distributional semantics techniques namely word2vec and JoBimText. The task of lexical expansion of words in Hindi is considered for the analysis. A manual similarity assessment of the lexical expansions of words is employed for evaluation of the techniques. It can be observed that word2vec framework performs better than the JoBimText for various corpus sizes. Analysis of the results also presents insights on performance of the systems on various word types.
Starting Page	39
Ending Page	42
Page Count	4
File Format	PDF
ISBN	9781450340045
DOI	10.1145/2838706.2838713
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-12-04
Publisher Place	New York
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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word2vec or JoBimText?: A Comparison for Lexical Expansion of Hindi Words