Indian Journal of Science and Technology

Abstract

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