www.astesj.com 1408 Recommendation System for SmartMart-A Virtual Supermarket Poonam Ghuli * , Manoj Kartik R, Mohammed Amaan, Mridul Mohta, N Kruthik Bhushan, Poonam Ghuli, Shobha G Department of Computer Science and Engineering, R V College of Engineering, Bengaluru,560059, India A R T I C L E I N F O A B S T R A C T Article history: Received: 15 October, 2020 Accepted: 26 November, 2020 Online: 16 December, 2020 The current online shopping system does not provide the actual shopping experience to the users where they scroll through the web pages and select an item to purchase, which becomes monotonous soon and lacks the shopping experience. This paper describes the development of the SmartMart, a 3D shopping mart where the user can navigate around the mart with the help of a virtual cart and interact with the products as they would do in real life. Further, this paper explains the integration of the recommendation system with the SmartMart that provides efficient and seamless customer experience. Here, the customers are recommended with various products based on their previous purchase history. This gives a more personalized touch to each user adding on to their shopping experience. This paper describes the implementation of recommendation system using three types of algorithms namely item-based collaborative filtering, popularity model and user- based collaborative filtering. These algorithms are integrated with Unity SmartMart application and tested with the open source dataset. This dataset is organized in three ways- original data, data with a dummy field and normalized data. Distance metrics such as Pearson co-relation co-efficient, Jaccard similarity, cosine similarity metrics are used to compute the similarity among customers. This paper presents a comparative study of these different similarity metrics for user-based recommendation algorithm based on precision, recall, F-value and accuracy. From results obtained it can be seen that the Pearson co- efficient metric gives the highest accuracy value (86.6%) but the F-value, mean precision and mean recall values are very less compared to Jaccard Similarity Metric. Hence, Jaccard similarity metric is preferred over Pearson co-relation co-efficient. The design and development of SmartMart along with the recommendation system adds a new dimension to both the existing online shopping system and provides better customer satisfaction. Keywords: 3D environment Unity Environment Collaborative Filtering Algorithm Recommendation system Online shopping 1. Introduction 3D simulation software provides a rich training experience to the user for various end-user applications, without using any physical asset and loss to the company. This is a key factor of 3D simulation that is expected to boost market growth. The simulation software market was valued at USD 8.24 billion in 2019, and it is expected to reach USD 19.22 billion, by 2025. The 3D simulation enables users to immerse in a computer-generated environment where they can interact with various simulated objects in a way replicating the real-life process. These 3D objects can be generated automatically or manually created by deformation of the mesh structure, or otherwise manipulating vertices. Using 3D simulation for online shopping primarily enhances the customer experience and takes online shopping to a new level of sublimity. This adds a realistic window which is absent with the existing online shopping websites where the user does not get to perceive the actual depiction of an item which they are inclined to purchase. Though the current websites try to minimize the hassle of the actual shopping process but it cuts away many privileges of a customer which would be helpful in selecting the appropriate item they want to purchase. Currently, the e-commerce websites display 2D images of the products and facilitates the text-based search to seek out desired items to be purchased. But this does not allow customers to associate themselves with the real-world object experience. So, to replicate the real-world shopping experience for customers, this paper describes the design and development of a 3D shopping mart ASTESJ ISSN: 2415-6698 * Corresponding Author: Poonam Ghuli, Department of Computer Science and Engineering, RV College of Engineering, 9986421230 & Email: poonamghuli@rvce.edu.in Advances in Science, Technology and Engineering Systems Journal Vol. 5, No. 6, 1408-1413 (2020) www.astesj.com https://dx.doi.org/10.25046/aj0506170