An efficient approach towards review analysis using NLP and Watson

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    A large collection of data is available over the internet which can be used to generate the needful relevant information according to individual needs. Even though the information given about an instance is enough to make a summary about it, the opinions and reviews updated by individuals regarding the instance give a clear idea of what the conclusion made by humankind is. So, analyzing reviews by Sentimental analysis help to identify the human opinion about an instance. Along with the reviews, the images uploaded by users showcase the real-time situations without any edits and can lead to a more specific conclusion. Images are analyzed with the tags generated from them using IBM WATSON. Therefore, taking in consideration both images and reviews will generate a well precise report about the instance. The review analysis is done by Naive Bayes Classifier which is considered as the best choice for text classification.

     

     


     

  • Keywords


    IBM WATSON; Naive Bayes Classifier; Review Analysis.

  • References


      [1] Introduction to Natural Language Processing (NLP) – Algorithmia Blog, [https://blog.algorithmia.com /introduction-natural-languageprocessing-nlp/].

      [2] Xiaojiang Lei, Xueming Qian, Guoshuai Zhao, “Rating Prediction Based on Social Sentiment from Textual Reviews”, IEEE Transactions on Multimedia (Volume: 18, Issue: 9, Sept. 2016), Page(s): 1910 - 1921.

      [3] Sentiment analysis, [https://viblo.asia/uploads/58039b5e-7d90-4165-9f0b-83fb77792318.jpg].

      [4] Chaitali Chandankhede, Pratik Devle, “ISAR: Implicit Sentiment Analysis of User Reviews”, 2016 International Conference on Computing, Analytics and Security Trends (CAST), College of Engineering Pune, India. Dec 19-21, 2016.

      [5] Deebha Mumtaza, Bindiya Ahujab, “Sentiment Analysis of Movie Review Data Using Senti-Lexicon Algorithm”, 2016 2nd International Conference on Applied and Theorectical Computing, 21-21 July 2016, Bangalore, India.

      [6] Akkamahadevi R Hanni, Mayur M Patil, Priyadarshini M Patil ,” Summarization of Customer Reviews for a Product on a website using Natural Language Processing”, 2016 Intl. Conference on Advances in Computing, Communications and Informatics (ICACCI), Sept. 21-24, 2016, Jaipur, India.


 

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Article ID: 15553
 
DOI: 10.14419/ijet.v7i2.33.15553




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