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Spatial Intelligence in E-Commerce: Integrating Mobile Agents with GISs for a Dynamic Recommendation System

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Vydáno v:Algorithms vol. 18, no. 1 (2025), p. 28
Hlavní autor: Shili, Mohamed
Další autoři: Hammedi, Salah, Elkhodr, Mahmoud
Vydáno:
MDPI AG
Témata:
Digital mapping
Customer services
Software
Agents (artificial intelligence)
Internet
Collaboration
Recommender systems
Spatial analysis
Communication
Context
Electronic commerce
Customization
Data collection
Distributed processing
Customers
Geography
Spatial data
Marketing
Design
Geographic information systems
Real time
Inventory
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Abstrakt:The evolving capabilities of Geographic Information Systems (GISs) are transforming various industries, including e-commerce, by providing enhanced spatial analysis and precision in customer targeting, and improving the ability of recommender systems. This paper proposes a novel framework that integrates mobile agents with GISs to deliver real-time, personalized recommendations in e-commerce. By utilizing the OpenStreetMap API for geographic mapping and the Java Agent Development Environment (JADE) platform for mobile agents, the system leverages both geospatial data and customer preferences to offer highly relevant product suggestions based on location and behaviour. Mobile agents enable real-time data collection, processing, and interaction with customers, facilitating dynamic adaptations to their needs. The combination of GISs and mobile agents enhances the system’s ability to analyze spatial data, providing tailored recommendations that align with user preferences and geographic context. This integrated approach not only improves the online shopping experience but also introduces new opportunities for location-specific marketing strategies, boosting the effectiveness of targeted advertising. The validation of this system highlights its potential to significantly enhance customer engagement and satisfaction through context-aware recommendations. The integration of GISs and mobile agents lays a strong foundation for future advancements in personalized e-commerce solutions, offering a scalable model for businesses looking to optimize marketing efforts and customer experiences.
ISSN:1999-4893
DOI:10.3390/a18010028
Zdroj:Engineering Database