Indian Journal of Science and Technology
Year: 2019, Volume: 12, Issue: 8, Pages: 1-6
K. Sasi Kala Rani1*, U. Susmitha1, D. Ramya1 and K. Sujatha1,2
1Department of Computer Science, Sri Krishna College of Engineering and Technology, Coimbatore - 641008, Tamil Nadu, India; [email protected], [email protected], [email protected], [email protected]
2Wenzhou Kean University, China.
*Author for correspondence
K. Sasi Kala Rani
Department of Computer Science, Sri Krishna College of Engineering and Technology, Coimbatore - 641008, Tamil Nadu, India.
Email: [email protected]
Objectives: To develop an enhanced web application, using web services for interconnecting social network, E-Commerce application and News channels. Products will be recommended based on customers’ preferences. Methods/Statistical Analysis: A three-tier methodology in which social network is the decision-making layer and E-commerce and news channel portals are the application layers. The social media layer will be analyzed using a method called as Text categorization which generates data for gathering user preferences. This information will be made as micro-blogging information. This will be passed on to other networks via Artificial Neural Network (ANN). Findings: The micro-blogging details are created at the tier one, Social network. This is then connected to e-commerce website and news portals. The micro-blogging information created will be purely based on users’ preferences, hobbies and other user data provided in the social network. These are further passed on to the e-commerce website to accurately recommend the products to individual users. Also, on the news portal, individual users can get notified about local news about their localities. Application/Improvements: This serves as a three-in-one application since there are three different tiers. Further improvements could be made by adding offline features. This could be improved by developing this as a separate mobile application.
Keywords: E-Commerce, Recommender System, Social Media, ANN
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