DressUp (Sentiment Analysis of Product Reviews)
| dc.contributor.author | Maaz Hussain | |
| dc.contributor.author | SP17-BSE-096 | |
| dc.contributor.author | Sobia Usman | |
| dc.contributor.author | LHR TP 7136 | |
| dc.date.accessioned | 2026-02-25T07:33:49Z | |
| dc.date.issued | 2021-11-20 | |
| dc.description.abstract | E-commerce is process of doing business through computer. A person can buy anything using computer. With increase in this business it enables everyone to sell their items on internet, so there are a lot of items on ecommerce sites with good and bad ratings and it is difficult for customer to find the best one. The aim of this project is to develop a clothing portal which helps customers to buy genuine and best rated products. By using machine learning approach, we have performed sentimental analysis of products rating and review (comments) and generate rating to fulfil customer satisfaction against products. We divide positive and negative rating so user can distinguish which product is better. Sentiment analysis uses NLP and text analysis (opinion mining) technique to identify rating from text. Many new companies perform sentiment analysis to understand the sentiments of people for their products to perform business analysis and increase sale. | |
| dc.identifier.uri | https://repository.cuilahore.edu.pk/handle/123456789/2248 | |
| dc.publisher | Library Information Services, COMSATS University Islamabad, Lahore Campus. | |
| dc.relation.ispartofseries | LHR TP 7136; LHR TP 7136 | |
| dc.subject | DressUp (Sentiment Analysis of Product Reviews) | |
| dc.subject | Computer science | |
| dc.subject | FA17 | |
| dc.subject | E-commerce | |
| dc.subject | clothing portal | |
| dc.title | DressUp (Sentiment Analysis of Product Reviews) | |
| dc.type | Thesis |
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