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INTERNATIONAL JOURNAL OF CREATIVE RESEARCH THOUGHTS - IJCRT (IJCRT.ORG)
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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
Call For Paper - Volume 12 | Issue 5 | Month- May 2024
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Published Paper Details:
Paper Title
COMPARATIVE ANALYSIS OF DEEP LEARNING TECHNIQUES FOR ASPECT LEVEL OPINION MINING
Authors
M.Ramesh, Dr.Bandla Srinivas Rao
Keywords
Aspect level opinion mining, customer reviews, deep learning, sentiment analysis, opinion mining
Abstract
Customer reviews seek to determine algorithmically the product aspects and their equivalent views from a assortment of opinions. Therefore, it is very important to create methods for the e-commerce, online shopping of online going to places of interest, which are very important to analyze the good amount of social data that are present on the Web routinely. Opinion mining is defined as mining and analyzing routinely from the text, big data and talk of opinions and reviews by means of various methods, views, emotions, and opinions. In this paper, different deep learning techniques are compared and discussed for mining online reviews those are placed by customers. Our major theme is the establishment of a scheme to analyze opinions that involve judging various consumer products.
IJCRT's Publication Details
Unique Identification Number - IJCRT2104417
Paper ID - 205956
Page Number(s) - 3364-3366
Pubished in - Volume 9 | Issue 4 | April 2021
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
M.Ramesh, Dr.Bandla Srinivas Rao, "COMPARATIVE ANALYSIS OF DEEP LEARNING TECHNIQUES FOR ASPECT LEVEL OPINION MINING", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.9, Issue 4, pp.3364-3366, April 2021, Available at :http://www.ijcrt.org/papers/IJCRT2104417.pdf
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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