Domain Independent Approach for Aspect Oriented Sentiment Analysis for Product Reviews

2017
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Authors: Nilesh Shelke; Shriniwas Deshpande; Vilas Thakare
Published in: Proceedings of the 5th International Conference on Frontiers in Intelligent Computing: Theory and Applications
Publisher: Springer Singapore

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Abstract

The Sentiment analysis from text documents is emerging field for the research in Natural Language Processing (NLP) and text mining. Feature specific opinion matters more than the overall opinion. Given a collection of review texts, the goal is to detect the individual product aspects comments by reviewers and to decide whether the comments are rather positive or negative. In this research paper unsupervised approach for domain independent feature specific sentiment analysis has been proposed. SentiWordNet lexical resource has been used to determine the polarity of identified features. Research work has shown the promising results over the previously used approaches using SentiWordNet. Newly introduced SentiWordNet 3.0 has been proved to be an important lexical resource.

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Title: Domain Independent Approach for Aspect Oriented Sentiment Analysis for Product Reviews
Authors: Nilesh Shelke
Shriniwas Deshpande
Vilas Thakare
Publisher: Springer Singapore
Book: Proceedings of the 5th International Conference on Frontiers in Intelligent Computing: Theory and Applications
Print ISBN: 978-981-10-3155-7

Electronic ISBN: 978-981-10-3156-4

Copyright Year: 2017
DOI: https://doi.org/10.1007/978-981-10-3156-4_69

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