Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/341153
Title: Aspect Level Sentiment Polarity Classification Using Sequence Attention Mechanism with Amplified Intelligence
Researcher: Sindhu C
Guide(s): Vadivu G
Keywords: Automation and Control Systems
Computer Science
Engineering and Technology
University: SRM University
Completed Date: 2021
Abstract: With the exploding web technology, user generated content is all over the web and is accessible almost everywhere in this world. Such an accessibility has paved way for an easier suggestion seeking paradigm. In this fast-paced world, we humans find no time to stand and stare, which well suits this scenario, where, we don t want to read through each and every review of a product or a service. Sentiment Analysis is, thus an inevitable process, which helps every manufacturer and brand-owner to analyse the pros and cons of his own item and his competing products. Furthermore, be it any service or product, the experience shared about it is multi-dimensional with loads of emotions splashed into it newline
Pagination: 
URI: http://hdl.handle.net/10603/341153
Appears in Departments:Department of Computer Science Engineering

Files in This Item:
File Description SizeFormat 
80_recommendation.pdfAttached File361.45 kBAdobe PDFView/Open
certificate page.pdf188.83 kBAdobe PDFView/Open
chapter 1.pdf1.12 MBAdobe PDFView/Open
chapter 2.pdf352.98 kBAdobe PDFView/Open
chapter 3.pdf827.4 kBAdobe PDFView/Open
chapter 4.pdf1.02 MBAdobe PDFView/Open
chapter 5.pdf896.31 kBAdobe PDFView/Open
chapter 6.pdf737.64 kBAdobe PDFView/Open
chapter 7.pdf194.5 kBAdobe PDFView/Open
curriculum vitae.pdf48.97 kBAdobe PDFView/Open
list of publications.pdf175.37 kBAdobe PDFView/Open
preliminary page.pdf327.91 kBAdobe PDFView/Open
references.pdf290.73 kBAdobe PDFView/Open
title page.pdf176.73 kBAdobe PDFView/Open
Show full item record


Items in Shodhganga are licensed under Creative Commons Licence Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).

Altmetric Badge: