A Software Factory for Accelerating the Development of Recommender Systems in Smart Tourism Mobile Applications: An Overview

Abstract

Recommender Systems (RSs) have become essential for suggesting personalized recommendations to users across various fields, especially in tourism. Due to the rising popularity of mobile devices, mobile RSs have emerged as a potential research area. However, developing these systems into smart tourism mobile applications requires a significant investment in artificial intelligence experts and software engineering. Hence, to reduce the cost of this investment, we propose building a software factory that provides a robust set of assets such as domain-specific languages for accelerating the development process. To this aim, we apply a model-driven engineering approach that uses models, metamodels, and model transformations to support the designing and implementation of these software systems. In this paper, we introduce an overview of our software factory to support the development of several models of RSs.

Keywords

• smart tourism
• recommender system
• software factory
• model-driven engineering
• domain-specific language
• model transformation