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Deep Learning-Based Frameworks for Aspect-Based Sentiment Analysis

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Deep Learning-Based Approaches for Sentiment Analysis

Part of the book series: Algorithms for Intelligent Systems ((AIS))

Abstract

Opinions are key influencers of almost all human practices. One can easily find a number of opinions about any product or services in the form of product reviews. These product reviews are available in a tremendous amount. It is not feasible or even impossible to go through each review and make a concise decision about any product. Aspect-based sentiment analysis (ABSA) comes as a solution to this problem. It gives an approach to examine online reviews and provides a summary based on these reviews. Machine learning techniques have been broadly utilized for ABSA. Recently with the evolution of processing power of computers and digitization of the society, deep learning is taking off. Deep learning methods produced state-of-the-art results in various NLP tasks without intensive feature engineering. In this chapter, we present an introduction about ABSA following a comprehensive overview of various deep learning models used in the field of ABSA.

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Correspondence to Ashish Kumar .

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Kumar, A., Sharan, A. (2020). Deep Learning-Based Frameworks for Aspect-Based Sentiment Analysis. In: Agarwal, B., Nayak, R., Mittal, N., Patnaik, S. (eds) Deep Learning-Based Approaches for Sentiment Analysis. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-1216-2_6

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  • DOI: https://doi.org/10.1007/978-981-15-1216-2_6

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