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MOCHA2018: The Mighty Storage Challenge at ESWC 2018 Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Evaluating Quality of Word Embeddings with Sentiment Polarity Identification Task

Authors : Vijayasaradhi Indurthi, Subba Reddy Oota

Published in: Semantic Web Challenges

Publisher: Springer International Publishing

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Abstract

Neural word embeddings have been widely used in modern NLP applications as they provide vector representation of words and capture the semantic properties of words and the linguistic relationship between the words. Many research groups have released their own version of word embeddings. However, they are trained on generic corpora, which limits their direct use for domain specific tasks. In this paper, we evaluate a set of pretrained word embeddings which were provided to us, on a standard NLP task - Sentiment Polarity Identification Task.

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previous chapter The FeatureSent System at ESWC-2018 Challenge on Semantic Sentiment Analysis
Footnotes
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Metadata
Title
Evaluating Quality of Word Embeddings with Sentiment Polarity Identification Task
Authors
Vijayasaradhi Indurthi
Subba Reddy Oota
Copyright Year
2018
Book
Semantic Web Challenges

Print ISBN: 978-3-030-00071-4

Electronic ISBN: 978-3-030-00072-1

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-030-00072-1_18