LOCAL-LOOP
Explainable multi-stakeholder recommendation system for smart tourism
Executive Architecture Summary
Contributed to an explainable multi-stakeholder recommendation system using simulation, multi-objective scoring and data-driven evaluation for smart tourism.
[01 // THE CHALLENGE & PROBLEM SPACE]
Traditional tourism recommendation algorithms optimize solely for user click-through rates, ignoring local municipal capacity, environmental carrying limits, and merchant fairness.
[02 // SYSTEM ARCHITECTURE & TOPOLOGY]
Python-based simulation pipeline utilizing weighted graph scoring engines and multi-stakeholder objective optimization matrices.
Technical Implementation & Engineering Approach
Formulated multi-objective scoring algorithms balancing user preferences with municipal sustainability criteria.
Constructed simulation models to evaluate recommendation distribution across diverse vendor networks.
Built explainable data pipelines generating transparent rationale for suggested itineraries and locations.
[03 // VERIFIED ENGINEERING OUTCOME & IMPACT]
Produced explainable, data-driven evaluation models proving equitable distribution of tourism traffic while maintaining high user satisfaction.