Abstract
In this paper, we study a critical problem in spatially based applications: personalised route recommendation, or PRR. Given a road network and users' route queries, the PRR task is to generate user-specific route suggestions. An old-fashioned approach is to tweak search algorithms to yield pathfinding-like results. These methods often focus on narrowing the search space by applying suitable heuristic strategies. Because heuristic strategies for these search algorithms are often built, they are not appropriate for application in scenarios involving complex tasks. Moreover, it is difficult to integrate useful background data into the search procedure. To produce a more principled solution, we propose to apply neural networks to improve search techniques for resolving the PRR issue, which is based on the well-known A* algorithm.
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