Tushar Samaniya,
Sankeeta Jha,
- Student, Department of Computer Science and Engineering. Echelon Institute of Technology, Faridabad, Haryana, India
- Assistant Professor, Department of Computer Science and Engineering Echelon Institute of Technology, Faridabad, Haryana, India
Abstract
This research work focuses on graph databases, mainly Neo4j databases, in recommendation systems for e-commerce websites. The importance of research is that it explains how graph databases efficiently handle the complex relationship between user-items, which is difficult for traditional databases. Sparsity, limited diversity, and high setup costs are the challenges traditional databases face. This research work overcomes these problems using Ne04j with Cypher query language and graph algorithms (PageRank, Shortest Path, Community Detection), which give real-time and personalized suggestions. There is use of data modelling (nodes, edges, properties), collaborative and content-based filtering, a hybrid approach, which includes Neo4j along with Deep learning (Graph Neural Networks) as a Methodology. The result of this research work is that these systems are fast, scalable, and accurate, like the “frequently bought together” suggestion in Amazon. These systems increase the user experience and business revenue, but privacy and scalability is still the challenging part.
Keywords: Graph database, algorithm, data modelling, deep learning, MySQL databases, E-commerce, amazon, Flipkart
[This article belongs to Journal of Advanced Database Management & Systems ]
Tushar Samaniya, Sankeeta Jha. An Analysis of Graph Database in Data Modelling and Analysis for a Recommendation System. Journal of Advanced Database Management & Systems. 2025; 12(03):33-39.
Tushar Samaniya, Sankeeta Jha. An Analysis of Graph Database in Data Modelling and Analysis for a Recommendation System. Journal of Advanced Database Management & Systems. 2025; 12(03):33-39. Available from: https://journals.stmjournals.com/joadms/article=2025/view=229327
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Journal of Advanced Database Management & Systems
| Volume | 12 |
| Issue | 03 |
| Received | 28/06/2025 |
| Accepted | 06/10/2025 |
| Published | 15/10/2025 |
| Publication Time | 109 Days |
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