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Discrepancy Detector - Novel approach for detecting discrepancy between a review comment and the review star rating

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dc.contributor.author Yeshan Santhush Indiketiya Hewage
dc.date.accessioned 2023-01-18T09:21:24Z
dc.date.available 2023-01-18T09:21:24Z
dc.date.issued 2022
dc.identifier.citation Indiketiya Hewage, Yeshan Santhush (2022) Discrepancy Detector - Novel approach for detecting discrepancy between a review comment and the review star rating. BSc. Dissertation, Informatics Institute of Technology en_US
dc.identifier.issn 2018050
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/1481
dc.description.abstract Amazon has been the most dominant Ecommerce platform when compared with its competitors such as Walmart and eBay. A vital aspect of the products being sold within such platforms is a review, in which a customer review is a form of expression from customers, expressing their thoughts and experiences with the products and the services. One of the main review inconsistencies is the discrepancy between the review comment and the review star rating, and this research focuses on identifying such discrepancy occurring reviews of Amazon using a novel technique. Past research has made use of various techniques to identify such inconsistent reviews. Like Machine Learning models, Comparison techniques, Conditional Techniques and Correlation techniques. The author evaluated DNN, CNN and LSTM, and choose the best performing model, and after optimization, the LSTM model was chosen, which performed with an accuracy of 99% and it was integrated to a web application, introducing the prototype ‘Discrepancy Detector’ to detect inconsistent reviews. en_US
dc.language.iso en en_US
dc.subject Ecommerce en_US
dc.subject Amazon Reviews en_US
dc.subject Deep Learning Models en_US
dc.title Discrepancy Detector - Novel approach for detecting discrepancy between a review comment and the review star rating en_US
dc.type Thesis en_US


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