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IJSDR
INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15

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Paper Title: A Survey on Opinion mining Techniques on Online Reviews
Authors Name: Sathyapriya.N , Akila.C
Unique Id: IJSDR1607015
Published In: Volume 1 Issue 7, July-2016
Abstract: Today's world is a world of Internet. All work can be done with the help of Internet. Internet has become a new source of entertainment, education, communication and shopping etc. Sentiment Analysis is a subfield of Natural Language Processing concerned with the determination of opinion about a product or topic. Sentiment Analysis also called Opinion Mining, which collects and examines opinions about the product made in blog posts, comments or reviews. Sentiment Analysis is à rapidly growing area. There are numerous e-commerce sites available on Internet which allows users to give feedback about specific products. Users post their feedbacks as reviews in the websites which is helpful for companies and other users. These reviews are analyzed to determine the opinion of the users about the objects. It is impossible to manually analyze those reviews. To overcome the problem, many algorithms are proposed for mining the opinions of the users. Algorithms enable us to extract opinions from the Internet and predict customer's preferences. This paper presents various techniques used for opinion classification by different authors and its accuracy in the classification of opinions.
Keywords: Accuracy, Algorithms, Opinion, Opinion Mining, Reviews, Techniques, Sentiment Analysis.
Cite Article: "A Survey on Opinion mining Techniques on Online Reviews", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.1, Issue 7, page no.70 - 74, July-2016, Available :http://www.ijsdr.org/papers/IJSDR1607015.pdf
Downloads: 000337070
Publication Details: Published Paper ID: IJSDR1607015
Registration ID:160586
Published In: Volume 1 Issue 7, July-2016
DOI (Digital Object Identifier):
Page No: 70 - 74
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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