In this paper, we introduce a new interesting path finding problem, which is the Skyline Trips of Multiple POIs Categories (
) query. In particular, given a road network with a set of Points of Interest (POIs) from different categories, a list of items the user is planning to purchase and a pricing function for items at each related POI; find the skyline trips in term of both trip length and trip aggregated cost. This query has important applications in everyday life. Specifically, it assists people to choose the most suitable trips among the skyline trips based on two dimensions; trip total length and trip aggregated cost. We prove the problem is NP-hard and we distinguish it from existing related problems. We also proposed a framework and two effective algorithms to efficiently solve the
query in real time and produce near optimal results when tested on real datasets.