Tour Enhance: A Novel Rule-Based Travel Planning System

Abstract

Tourism significantly contributes to economic growth, particularly evident from China’s rapid post-recovery increase in travel demand. This surge underscores the necessity for accessible, well-organized tourist information. Given the vast number and broad distribution of tourist sites, intelligent filtering and visualization of these locations are crucial. This paper introduces Tour Enhance, an interactive system designed to dynamically exchange information between the system and its users. Unlike traditional static methods, Tour Enhance utilizes real-time processing to tailor travel recommendations to individual user preferences, thereby improving user engagement and satisfaction. This study undertakes three key tasks: statistical analysis and visualization of tourist data, rule-based recommendation generation, and user survey-based evaluation of these recommendations. The effectiveness of Tour Enhance was assessed through a user study with 57 participants, who highly rated the system on interface usability, functionality, and accuracy of recommendations. The results demonstrate that Tour Enhance effectively enhances the travel planning process, highlighting the significant advantages of integrating interactive systems and personalized data visualization in tourism. This research contributes to the advancement of human-computer interaction applications in tourism and lays the groundwork for future studies focused on enhancing user experiences through technological innovations.