Employing user feedback for semantic location services

Just as coordinate-oriented location-based applications have exploded recently with mapping services, new semantic location services will be critical for the next wave of killer applications. People are going to want everyday applications to have location-awareness that goes beyond simple numerical latitude and longitude. Loci is a new semantic location service layer that employs user feedback to bridge the gap between machine-learned and human-defined places. Advances in place learning techniques have provided us the tools to detect nearly 95% of the visits we make to places and the distances we travel. The difficulty of recovering the remaining 5% comes from designing parameters that work for every user in every place. Based on a user study with 29 participants over three weeks, we show that the level of user feedback required by the service is acceptable and most of the users are willing to provide help to improve their experiences with the service. Our results suggest that user feedback has the potential to significantly improve semantic location services, but requires well-timed prompting mechanisms to improve the quality of the feedback.