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| Open Access | E-COMMERCE RECOMMENDATIONS THROUGH GEOGRAPHIC CONTEXT AND POPULATION CHARACTERISTICS
Abstract
Recommender systems are integral to the success of modern e-commerce platforms, guiding users to products and services that align with their preferences. While traditional systems often rely on past purchase behavior or content similarity, the increasing ubiquity of location-based services presents a significant opportunity to infuse geographic context into recommendation logic. This article presents a comprehensive overview of how geographic information, particularly in relation to population characteristics, can enhance e-commerce recommender systems. We explore methodologies for integrating spatial data, discuss the architectural implications, and analyze the benefits and challenges of developing location-aware recommendation strategies. Our review synthesizes existing research on point-of-interest (PoI) recommendations, location-based services, and geospatial information systems (GIS) within e-commerce, highlighting the potential for hyper-personalized experiences and localized business growth. We conclude by outlining key research gaps and future directions for leveraging geographic and demographic data to optimize e-commerce recommendations.
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Authors retain the copyright of their manuscripts, and all Open Access articles are disseminated under the terms of the Creative Commons Attribution License 4.0 (CC-BY), which licenses unrestricted use, distribution, and reproduction in any medium, provided that the original work is appropriately cited. The use of general descriptive names, trade names, trademarks, and so forth in this publication, even if not specifically identified, does not imply that these names are not protected by the relevant laws and regulations.