An Automated Approach for Deriving Semantic Annotations of Tourism Products based on Geospatial Information

High quality product data is a necessary prerequisite for supporting efficient browsing and recommendation procedures on e-commerce platforms. This is especially true for the tourism domain where an abundance of information can easily overwhelm users. Although classification data such as to which category (e.g. accommodation, restaurant or sight) a tourism product belongs is usually directly available, qualitative information, such as proximity to a lake or opportunities for dining or shopping, is rarely provided in a structured way. As a consequence, users can not restrict their search on these criteria; rather, it would require costly manual information acquisition efforts. In this paper we propose a knowledge-based approach that automatically associates such qualitative concepts with tourism products based on their geographic coordinates and their spatial proximity. An initial evaluation of the approach that considered automatically generated annotations within different regions suggests that it can be used as an alternative to domain experts.