Semantic Positioning - An Innovative Approach for Providing Location-Based Services Based on the Web of Data

摘要

Conventional positioning approaches for Location-based Services (LBS) such as those provided by Google and Apple, are solely driven by geometric spatial data. Especially in proactive LBS scenarios, in which users are notified as soon as they reach a certain area, locations are mostly defined by geofences and do not incorporate any further information from the semantics of the location, such as the points of interest in the vicinity or more detailed information about the district the user is in. Leveraging LBS with the extensive pool of interconnected data in the Linking Open Data (LOD) Cloud will improve the LBS experience and will enable the development of sophisticated proactive services. In this paper, we present a Semantic Positioning Platform that enhances classic positioning methods by semantic features. This platform utilizes the OpenMobileNetwork, which is a Live Crowd sourcing Platform providing static as well as dynamic mobile network topology data based on the principles of Linked Data. It further uses the Positioning Enabler that enables persistent user background tracking and subscription to Semantic LBS Services. The Semantic Positioning approach allows LBS providers to locate users with respect to the semantics of their position instead of defining spatial geofences. As a proof-of-concept, a Restaurant Recommender Service is presented and its applicability is evaluated.