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2023 | OriginalPaper | Chapter

Sentiment Analysis and Vector Embedding: A Comparative Study

Authors : Shila Jawale, S. D. Sawarkar

Published in: Smart Trends in Computing and Communications

Publisher: Springer Nature Singapore

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Abstract

Automatic intent/sentiment classification can be done with various machine learning approaches as well as methods. But the success of these techniques majorly depends on the representation of words or documents in vector space. That can be easily consumed by machine toward learning the hidden pattern of text/corpus. To achieve this, various methods have been proposed, and many are commercially accepted as well. In deep learning architecture for intent/sentiment analysis, the vector embedding plays a crucial role. It represents feature extraction. In this paper, various methods for vector embedding are discussed along with their comparison.

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Title: Sentiment Analysis and Vector Embedding: A Comparative Study
Authors: Shila Jawale
S. D. Sawarkar
Publisher: Springer Nature Singapore
Book: Smart Trends in Computing and Communications
Print ISBN: 978-981-16-9966-5

Electronic ISBN: 978-981-16-9967-2

Copyright Year: 2023
DOI: https://doi.org/10.1007/978-981-16-9967-2_30

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