HyRA: A Hybrid Recommendation Algorithm Focused on Smart POI. Ceutí as a Study Scenario.

Area of Science:

• Computer Science
• Information Systems
• Tourism Technology

Background:

• The proliferation of mobile devices, GPS, and Social Networking Sites (SNS) enables users to share rich tourist experiences online.
• Contextual information from these technologies significantly enhances the tourism domain.

Purpose of the Study:

• To propose and develop an algorithm for recommending Smart Points of Interaction (Smart POIs) tailored to individual user preferences and POI context.
• To enhance personalized tourism experiences through intelligent recommendations.

Main Methods:

• A novel Hybrid Recommendation Algorithm (HyRA) was developed.
• HyRA integrates an aggregation operator into user-based Collaborative Filtering (CF).
• The algorithm incorporates Smart POI categories and geographical data.

Main Results:

• Two real-world datasets were collected and preprocessed, alongside a Smart POIs' categories dataset.
• Experimental datasets include 16 Smart POIs, 200 user preference responses, and 13 Smart POI categories.
• Experimental results indicate promising performance for HyRA's recommendations.

Conclusions:

• The developed HyRA algorithm shows potential for effective personalized Smart POI recommendations.
• The integration of user preferences, context, and item attributes improves recommendation accuracy in tourism.