Personalized Route Recommendation with Neural Network Enhanced A* Search Algorithm

Jingyuan Wang, Ning Wu, Xin Zhao
2021 IEEE Transactions on Knowledge and Data Engineering  
In this work, we study an important task in location-based services, namely Personalized Route Recommendation (PRR). Given a road network, the PRR task aims to generate user-specific route suggestions for replying to users' route queries. A classic approach is to adapt search algorithms to construct pathfinding-like solutions. These methods typically focus on reducing search space with suitable heuristic strategies. For these search algorithms, heuristic strategies are often handcrafted, which
more » ... re not flexible to work in complicated task settings. In addition, it is difficult to utilize useful context information in the search procedure. To develop a more principled solution to the PRR task, we propose to improve search algorithms with neural networks for solving the PRR task based on the widely used A * algorithm. The main idea of our solution is to automatically learn the cost functions in A * algorithms, which is the key of heuristic search algorithms. Our model consists of two main components. First, we employ attention-based Recurrent Neural Networks (RNN) to model the cost from the source to the candidate location by incorporating useful context information. Instead of learning a single cost value, the RNN component is able to learn a time-varying vectorized representation for the moving state of a user. Second, we propose to use an estimation network for predicting the cost from a candidate location to the destination. For capturing structural characteristics, the estimation network is built on top of position-aware graph attention networks. The two components are integrated in a principled way for deriving a more accurate cost of a candidate location for the A * algorithm. Extensive experiment results on three real-world datasets have shown the effectiveness and robustness of the proposed model.
doi:10.1109/tkde.2021.3068479 fatcat:t7pf5eyi2jbyvmezdr6c5h5l34