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Online Product Review analysis for Sentiments

Ishan Arora1 , Gagandeep Singh2 , Lokesh Kumar3

  1. Computer Science, PSIT College Of Engineering, APJ Abdul Kalam Technical University, Kanpur, India.
  2. Computer Science, School of Engineering & Technology, Poornima University, Jaipur, India.

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-5 , Page no. 1045-1048, May-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i5.10451048

Online published on May 31, 2018

Copyright © Ishan Arora, Gagandeep Singh, Lokesh Kumar . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Ishan Arora, Gagandeep Singh, Lokesh Kumar, “Online Product Review analysis for Sentiments,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.1045-1048, 2018.

MLA Style Citation: Ishan Arora, Gagandeep Singh, Lokesh Kumar "Online Product Review analysis for Sentiments." International Journal of Computer Sciences and Engineering 6.5 (2018): 1045-1048.

APA Style Citation: Ishan Arora, Gagandeep Singh, Lokesh Kumar, (2018). Online Product Review analysis for Sentiments. International Journal of Computer Sciences and Engineering, 6(5), 1045-1048.

BibTex Style Citation:
@article{Arora_2018,
author = {Ishan Arora, Gagandeep Singh, Lokesh Kumar},
title = {Online Product Review analysis for Sentiments},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2018},
volume = {6},
Issue = {5},
month = {5},
year = {2018},
issn = {2347-2693},
pages = {1045-1048},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2106},
doi = {https://doi.org/10.26438/ijcse/v6i5.10451048}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i5.10451048}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2106
TI - Online Product Review analysis for Sentiments
T2 - International Journal of Computer Sciences and Engineering
AU - Ishan Arora, Gagandeep Singh, Lokesh Kumar
PY - 2018
DA - 2018/05/31
PB - IJCSE, Indore, INDIA
SP - 1045-1048
IS - 5
VL - 6
SN - 2347-2693
ER -

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Abstract

Buying and selling of things are a major part of human’s since early ages , but with the development of the online market the trade got shifted from usual market to online for ease of everyone .Internet (www) has been a resource to get the user’s review about the particular thing he had purchased. There are 2.4 billion active online users, who write and read online and use internet around us [1]. It will also help the companies to know what the problem the customers are facing in their use of the product. This will help the company to make better product and will surely help the customer to buy a product will large positive value [2]. With the help of the given system we classify the reviews. The paper will try to compare the various technique used to find out the opinion of the users .The proposed System will use the general algorithms of AI to find out the answer to this problem which are described in details in this paper.

Key-Words / Index Term

Sentiment Analysis, Naïve Bayes, Random Forest

References

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