Litcius/Paper detail

Enhanced Product Recommendations based on Seasonality and Demography in Ecommerce

K. Keerthika, T. Saravanan

20202020 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN)26 citationsDOI

Abstract

Today, the social network environments are trending to list the customers with the product recommendations. The social recommendations are generated by recommender system based on product ratings and comments. There has been number of work towards improving the accuracy of recommendations generated by recommender systems. These tend to make the system to narrow the suggestion of product variety. The system should get evolved to the trend of generating diversity of recommendation so that the customer can explore the wide variety of products. The diversity of user demographic in social network makes the recommendation system can be applied to introduce variety of product recommendation. The seasonality of product is emerging trend in recommendation system to actively seek out the right product at right time. The work focuses on investigating the efficiency of recommender system, in generating the diverse suggestions for E-commerce dataset.

Topics & Concepts

Recommender systemVariety (cybernetics)Product (mathematics)Computer scienceDiversity (politics)Social network (sociolinguistics)Work (physics)Data scienceWorld Wide WebSocial mediaArtificial intelligenceEngineeringGeometrySociologyAnthropologyMathematicsMechanical engineeringRecommender Systems and TechniquesImage Retrieval and Classification TechniquesText and Document Classification Technologies