Interactive route personalization using regions of interest

There is an abundance of services and applications that find the most efficient route between two places, people are not always interested in efficiency; sometimes we just want a pleasant route. Such routes are subjective though, and may depend on contextual factors that route planners are oblivious to. One possible solution is to automatically learn what a user wants, but this requires behavioral data, leading to a cold start problem. An alternative approach is to let the user express their desires explicitly, effectively helping them create the most pleasant route themselves. In this paper we provide a proof of concept of a client-side route planner that does exactly that. We aggregated the Point of Interest information from OpenStreetMap into Regions of Interest, and published the results on the Web. These regions are described semantically, enabling the route planner to align the user’s input to what is known about their environment. Planning a 3 km long pedestrian route through a city center takes 5 s, but subsequent adjustments to the route require less than a second to compute. These execution times imply that our approach is feasible, although further optimizations are needed to bring this to the general public

A graph representation for verbal indoor route descriptions

Verbal indoor route descriptions contain human spatial knowledge that this paper aims to represent formally for further analysis and question-answering. Available tools - route graphs for route descriptions, and place graphs for place descriptions - both turn out to fall short on our corpus of verbal indoor route descriptions. Hence, the paper will identify the characteristics of indoor route descriptions, identify strategies for knowledge extraction, and seek a unified graph representation