Abstract:
People buy things from E-commerce sites. E-commerce companies couldn’t tell if clients liked their services from online buying. This motivates us to create a system where customers can leave reviews of products and online shopping services, which helps E-commerce companies and manufacturers improve service and products by mining client reviews.
An algorithm could track and manage consumer reviews by extracting internet reviews’ themes and sentiment. This technology lets users browse and buy things online. Customer reviews merchandise and online purchasing. The customer review keywords will be mined and compared to database keywords to rate the enterprise’s products and services.
This system will mine keywords via text mining. The system reviews user reviews to determine whether the E-commerce enterprise’s items and services are good, terrible, or worst. We score user reviews using a database of sentiment-based keywords with positivity or negativity weight.
This web application lets users browse things, buy them online, and evaluate them. Many E-commerce companies will use client reviews to improve or maintain their services and merchandise.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
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