Abstract: This paper presents a recommender system for both taxi drivers and people expecting to take a taxi, using the knowledge of 1) passengers' mobility patterns and 2) taxi drivers' picking-up/dropping-off behaviors learned from the GPS trajectories of taxicabs. The objective of this paper is, 1) it provides taxi drivers with some locations and the routes to these locations, towards which they are more likely to pick up passengers quickly (during the routes or in these locations) and maximize the profit of the next trip. 2) It recommends people with some locations (within a walking distance) where they can easily find vacant taxis. In our method, we learn the above-mentioned knowledge (represented by probabilities) from GPS trajectories of taxis. We feed the knowledge into a probabilistic model which estimates the profit of the candidate locations for a particular driver based on where and when the driver requests the recommendation.
Keywords- Location-based services, recommender systems, trajectories, taxicabs, parking place detection
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