UGC Approved Journal no 63975

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 8 Issue 7
July-2021
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

7.95 impact factor calculated by Google scholar

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Published Paper ID:
JETIR2107413


Registration ID:
312660

Page Number

d191-d202

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Title

A Product Review System using Sentiment Analysis with Cuckoo Search and Deep Learning Technique

Abstract

In last two decades, the explosion of e-commerce websites provide a lot of information to users for better analysis about anything. Millions of people express uninhibited opinions in terms of text about various product based on their features and e-commerce company status. This process forms an active feedback system which is of importance not only to the companies developing the products, but also to their rivals and several other potential customers those are trusted on online shopping. In this research, we present a method to analyze the product review based on available sentiment and model is known as a product review system using sentiment analysis with Swarm-based Cuckoo Search (SCS) and Artificial Neural Network (ANN) as deep learning technique. The objective of this research is identifying a set of potential features form text review data using the Lexicon-based feature extraction and SCS helps to select a set of optimal feature using the novel fitness function. Sentiment analysis in e-commerce company play a vital role to automatic extra the review polarity and arrange the review according to the polarity such as positive, negative and neutral. The extraction subjective information from reviews on the e-commerce site, social sites have gained greater attention from the data mining community but there management and fast response is still a big problem. To solve this problem, we present an intelligent system, which used a lexicon dictionary for text data polarity extraction and then SCS helps to select optimal feature form these and the experimental analysis shows that the effectiveness of system by comparing with state-of arts works in terms of performance.

Key Words

Sentiment Analysis, Product Review, E-commerce Company, Lexicon Dictionary, Swarm-based Cuckoo Search, Artificial Neural Network

Cite This Article

"A Product Review System using Sentiment Analysis with Cuckoo Search and Deep Learning Technique ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 7, page no.d191-d202, July-2021, Available :http://www.jetir.org/papers/JETIR2107413.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"A Product Review System using Sentiment Analysis with Cuckoo Search and Deep Learning Technique ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 7, page no. ppd191-d202, July-2021, Available at : http://www.jetir.org/papers/JETIR2107413.pdf

Publication Details

Published Paper ID: JETIR2107413
Registration ID: 312660
Published In: Volume 8 | Issue 7 | Year July-2021
DOI (Digital Object Identifier):
Page No: d191-d202
Country: Shri Muktsar sahib, Punjab, India .
Area: Engineering
ISSN Number: 2349-5162


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