Route Recommendations on Road Networks for Arbitrary User Preference Functions

Several services today are annotated with points of interest (Pols) such as coffee shop, park, etc. In this paper, we study the query where a user provides a set of relevant Pots and wants to identify the optimal route covering these Pots. Ideally, the route should be small in length so that the user can conveniently explore the Pots. On the other hand, the route should cover as many of the input Pots as possible. These conflicting requirements of the optimal route raise an intriguing question: how do you balance the importance of route length vs. PoI coverage? If the route is to be covered on foot, and it is raining, length is critical for convenience. On the other hand, if the weather conditions are good, or the user is equipped with a vehicle, coverage is more important. In essence, the relative importance depends on several latent factors and we solve this dilemma through skyline route queries. Skyline routes subsume the choice of the optimization function for a route since the optimal route for any rational user is necessarily a part of the skyline set. Our analysis reveals that the problem is NP-hard. We overcome this bottleneck by designing an algorithm called SkyRoute. SkyRoute drastically prunes the search space through a goal-directed search, which is further empowered by Lipschitz embedding, and provides up to 4 orders of magnitude speed-up over baseline techniques.