Adaptive tourist recommendation system: conceptual frameworks and implementations

Abstract

Recommendation systems and adaptive systems have been introduced in travel applications to support the travelers in their decision-making processes. These systems should respond to the unexpected changes during the travel. As a result, the first step is to sense the traveler's specifications, needs, and preferences before, during, and after the travel. Moreover, they should gather information about the accommodations, flights, cities, activities, and destinations through the different sources. In the next stage, these systems should provide personalized information. However, current tourist systems are not able to collect all travelers and travel products information from different resources. In addition, they failed to provide a sequence of recommendation on the different travel products (i.e., main destination, desired budget, length of travel, accommodation, transportation, activity, and restaurant) based on the traveler order preferences and travel stage. These systems do not support any customization. For instance, expert traveler or system admin could not change the recommendation algorithm settings anymore. To address these problems and issues, we propose and implement an adaptive tourist recommendation system that is supported by an adaptive tourist recommendation framework, process, architecture, and system.