An efficient approach towards review analysis using NLP and Watson
DOI:
https://doi.org/10.14419/ijet.v7i2.33.15553Published:
2018-06-08Keywords:
IBM WATSON, Naive Bayes Classifier, Review Analysis.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.
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 Reviewsâ€, 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 Reviewsâ€, 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 Algorithmâ€, 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 Processingâ€, 2016 Intl. Conference on Advances in Computing, Communications and Informatics (ICACCI), Sept. 21-24, 2016, Jaipur, India.
How to Cite
License
Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution Licensethat allows others to share the work with an acknowledgement of the work''s authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal''s published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
Accepted 2018-07-13
Published 2018-06-08