Architecting Next-Generation Tourism Recommendation Systems: A Knowledge Graph Approach

Abstract

This work focuses on exploring the way to adopt Knowledge Graph technologies to innovate Tourism Recommendation Systems (TRS) for which the existing problem is on the aspects of data modularity and the capacity of algorithms. Using the conceptual framework of the Knowledge Graphs, complex relationships between the entities in the tourism domain can be better captured and used to improve the recommended actions’ accuracy and relevance. In this way, Knowledge Graphs facilitate semantic understanding and real-time data integration to adapt TRS to the specific users’ preferences and contextual characteristics. The paper aims at presenting different use cases of Knowledge Graphs in the context of TRS and the primary benefit they offer is the integration of different data sources to enhance the analysis process that helps travellers. Some major conclusions emphasize the role of Knowledge Graphs for extending TRS architecture, as well as analysing tendencies and further innovations to plans for recommendation in tourism. Finally, this research is valuable in the development of the theoretical foundation of TRS by assimilating recent IT advances to improve the level of satisfaction and quality of the travel experience.