Integrated knowledge graph construction framework for places-of-interest retrieval using a property graph database

Abstract

With recent technological advances, the efficient extraction and utilization of valuable information from large-scale data sources have become increasingly important. The development of knowledge graphs (KGs) based on logical relationships between data has garnered attention from various location-related services. To provide results that satisfy the diverse preferences of individuals, explicit attributes and implicit semantic context must be considered during the retrieval of places of interest (POIs). Most POI retrievals often involve not just examining detailed information about places but also specifying places for intended visits. Therefore, spatial knowledge regarding the surroundings of POIs, such as proximity and accessible routes, should be incorporated to support decision-making. In this study, we propose a comprehensive framework for constructing a KG for POI retrieval (PKG), which adeptly integrates the place attributes, semantic features, and spatial context of locations. The core objective of this framework is to acquire suitable data for facilitating POI retrieval that effectively considers diverse user preferences for places. After constructing a PKG of Orlando (FL, USA), we verified the practical applicability of the proposed framework by conducting 10 types of distinct POI retrieval queries catering to a range of user preferences. The graph queries returned a list of POIs that precisely aligned with the requirements of users on not only the explicit attributes of places but also the spatial and semantic features while providing detailed travel route information to these destinations. In conclusion, the PKG enabled POI retrieval that satisfied user preferences and diversified the retrieved places and the information provided. As the PKG offers flexibility in data integration without physical constraints, it can be expanded by incorporating information from various sources.