Campus Cravings: A Campus Focused Food and Essentials Delivery Platform with Personalized Recommendations using GNN

Campus Cravings is an initiative meant to enable the delivery of food and provisions like stationery to institutions of learning. It promotes added convenience and well-being through a friendly, dependable, and effective service for delivery and ordering. With a centralized web-based platform, the system will overcome challenges of restricted access to varied products and time for students and workers. A central aspect of Campus Cravings is incorporating Graph Neural Networks (GNNs) for driving customer-specific recommendations. Modelling user relationships, products, and purchase history as a graph, the GNN supports precise and up-to-date suggestions based on individual likings for enhancing user interaction and order satisfaction. In addition to recommendation, the platform focuses on logistics optimization, order management, and scalability to address the changing needs of campus communities. Experimental outcomes indicate better access to essentials and beneficial effects on campus life in general.

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Publication Details

Journal
INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH
Published
2025-10-01
DOI
https://doi.org/10.56975/ijedr.v13i4.302009
Primary Topic
Recommender Systems and Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Campus Cravings: A Campus Focused Food and Essentials Delivery Platform with Personalized Recommendations using GNN

INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH
Recommender Systems and Techniques
article

Campus Cravings: A Campus Focused Food and Essentials Delivery Platform with Personalized Recommendations using GNN

article en

Abstract

Campus Cravings is an initiative meant to enable the delivery of food and provisions like stationery to institutions of learning. It promotes added convenience and well-being through a friendly, dependable, and effective service for delivery and ordering. With a centralized web-based platform, the system will overcome challenges of restricted access to varied products and time for students and workers. A central aspect of Campus Cravings is incorporating Graph Neural Networks (GNNs) for driving customer-specific recommendations. Modelling user relationships, products, and purchase history as a graph, the GNN supports precise and up-to-date suggestions based on individual likings for enhancing user interaction and order satisfaction. In addition to recommendation, the platform focuses on logistics optimization, order management, and scalability to address the changing needs of campus communities. Experimental outcomes indicate better access to essentials and beneficial effects on campus life in general.

INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCHVol. 13(4)
Parul University (IN)
Zero hunger
Openalex Percentile: Top 33%
Recommender Systems and Techniques
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