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Feature based Sentiment Analysis of Product Reviews using Deep Learning Methods
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 184 - Number 35 |
| Year of Publication: 2022 |
| Authors: Pramila Lovanshi, Chetan Gupta |
10.5120/ijca2022922443
|
Pramila Lovanshi, Chetan Gupta . Feature based Sentiment Analysis of Product Reviews using Deep Learning Methods. International Journal of Computer Applications. 184, 35 ( Nov 2022), 21-27. DOI=10.5120/ijca2022922443
Abstract
In web-based item audits clients examine about items and its highlights. An item might have hundreds or thousands of surveys, customers share their experience about items and remarks about items qualities. These item audits might have positive or negative opinions. A positive feeling contains great assessment on item and its elements correspondingly a pessimistic opinion tells disadvantages and issues of item and its highlights. Elements or angles are important for the item or its attributes. In this study we utilized highlight/viewpoint based opinion examination and a few strategies for breaking down the feelings communicated in web-based item surveys about the different elements of items.
References
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