Kalaivani, M. S. and Jayalakshmi, S. (2022) A Novel Approach for Sentiment Classification by Using Convolutional Neural Network. In: Proceedings of Second International Conference on Sustainable Expert Systems. Springer, pp. 143-152.
Full text not available from this repository. (Request a copy)Abstract
Social media platforms facilitate communication and data exchange. There is a substantial number of opinionated information available in digital form. It is essential to validate unstructured Web data in order to extract knowledge from it. Sentiment analysis offers a wide variety of applications across all domains. The primary objective of sentiment analysis is to asses if the input text is positive or negative. When a buyer purchases a product, they submit feedback of the product. These reviews are essential for getting a general sense of how people feel about the product or service. Customer reviews on the Internet help to make purchases. Sentiment analysis results assist businesses, understand customer expectations, and enhance service and product quality. Several deep learning algorithms have been used in this sector with promising results. This paper suggests a deep learning approach for sentiment analysis by using convolutional neural networks.
Item Type: | Book Section |
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Subjects: | Computer Science Engineering > Neural Network |
Divisions: | Computer Applications |
Depositing User: | Mr IR Admin |
Date Deposited: | 25 Sep 2024 05:49 |
Last Modified: | 25 Sep 2024 05:49 |
URI: | https://ir.vistas.ac.in/id/eprint/7170 |