TY - EJOU AU - Liu, Yizhi AU - Wang, Xuesong AU - Liu, Jianxun AU - Liao, Zhuhua AU - Zhao, Yijiang AU - Wang, Jianjun TI - An Entropy-Based Model for Recommendation of Taxis’ Cruising Route T2 - Journal on Artificial Intelligence PY - 2020 VL - 2 IS - 3 SN - 2579-003X AB - Cruising route recommendation based on trajectory mining can improve taxidrivers' income and reduce energy consumption. However, existing methods mostly recommend pick-up points for taxis only. Moreover, their performance is not good enough since there lacks a good evaluation model for the pick-up points. Therefore, we propose an entropy-based model for recommendation of taxis' cruising route. Firstly, we select more positional attributes from historical pick-up points in order to obtain accurate spatial-temporal features. Secondly, the information entropy of spatial-temporal features is integrated in the evaluation model. Then it is applied for getting the next pick-up points and further recommending a series of successive points. These points are constructed a cruising route for taxi-drivers. Experimental results show that our method is able to obviously improve the recommendation accuracy of pick-up points, and help taxi-drivers make profitable benefits more than before. KW - Trajectory data mining KW - location-based services (LBS) KW - optimal route recommendation KW - pick-up point recommendation KW - information entropy DO - 10.32604/jai.2020.010620