Authors:
Rajkumar Rajasekaran, A. Jayaram Reddy, J. Kamalakannan, K. Govinda 

Addresses:
1,4School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India. 2,3School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Vellore, Tamil Nadu, India. vitrajkumar@gmail.com1, ajayaramreddyreddy@vit.ac.in2, jkamalakannan@vit.ac.in3, kgovinda@vit.ac.in4

Abstract:

Recommender systems can be described as algorithms that are designed with the aim of suggesting relevant and most-used items to users (movies, products, videos, books, electronics, etc.). The whole system is meant to follow the user/customer’s browsing tactics and find out the most relevant. In the present world of e-commerce, where every product is available online, users, as well as businesses, need an algorithm that can suggest items based on their category and the buyer’s preference. These algorithms can be made to suit any category of products. The algorithm implemented in this system will help readers all around the world find books relevant to their choice (preferred genre) and other users’ ratings. The recommendation system has been built on a NoSQL Graph Database. The main advantage of using Neo4J is that it captures the relationship between the data and similarity between items on the basis of the type and the preference of the user and also records the behaviour of data. There are various factors that can affect the recommendation system; we have considered users’ favourite genres and similar types of items. Since it is a graph database, it is easy for any person to analyze and visualize the relationships between different nodes and also manage huge amounts of data with ease.

Keywords: Book Recommendation System; NoSQL Graph Database; Huge Amount of Data; Neo4j; Querying Relational Database; World of E-Commerce; Category of Products; Property Graph Data Model.

Received on: 05/01/2023, Revised on: 02/03/2023, Accepted on: 21/04/2023, Published on: 05/05/2023

FMDB Transactions on Sustainable Computer Letters, 2023 Vol. 1 No. 2, Pages: 103-114

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