假装是你 发表于 2025-3-28 15:41:28
Ridesharing Recommendation: Whether and Where Should I Wait?r, we propose a recommendation framework to predict and recommend whether and where should the users wait to rideshare. In the framework, we utilize a large-scale GPS data set generated by over 7,000 taxis in a period of one month in Nanjing, China to model the arrival patterns of occupied taxis fro存在主义 发表于 2025-3-28 21:22:56
http://reply.papertrans.cn/103/10218/1021727/1021727_42.png内阁 发表于 2025-3-29 00:16:25
Keyword-aware Optimal Location Query in Road Network a client often wants to find a residence such that the sum of the distances between this residence and its nearest facilities is minimal, and meanwhile the residence should be on one of the client-selected road segments (representing where the client prefers to live). The facilities are categorizedGRAIN 发表于 2025-3-29 06:58:38
http://reply.papertrans.cn/103/10218/1021727/1021727_44.png支柱 发表于 2025-3-29 11:06:21
http://reply.papertrans.cn/103/10218/1021727/1021727_45.png繁重 发表于 2025-3-29 14:54:52
Point-of-Interest Recommendations by Unifying Multiple Correlations framework for location-aware recommender systems with the consideration of social influence, categorical influence and geographical influence for users’ preference. In the framework, we model the three types of information as functions following a power-law distribution, respectively. And then we u险代理人 发表于 2025-3-29 16:42:16
Top-, Team Recommendation in Spatial Crowdsourcingd Gmission, are getting popular. Most existing studies assume that spatial crowdsourced tasks are simple and trivial. However, many real crowdsourced tasks are complex and need to be collaboratively finished by a team of crowd workers with different skills. Therefore, an important issue of spatial c高贵领导 发表于 2025-3-29 22:00:39
http://reply.papertrans.cn/103/10218/1021727/1021727_48.pngPelvic-Floor 发表于 2025-3-30 01:27:24
Explicable Location Prediction Based on Preference Tensor Modelre personal services, the applications like location-aware advertising and route recommendation are interested not only in the predicted location but its explanation as well. In this paper, we investigate the problem of Explicable Location Prediction (ELP) from LBSN data, which is not easy due to th出生 发表于 2025-3-30 07:41:31
Explicable Location Prediction Based on Preference Tensor Modelre personal services, the applications like location-aware advertising and route recommendation are interested not only in the predicted location but its explanation as well. In this paper, we investigate the problem of Explicable Location Prediction (ELP) from LBSN data, which is not easy due to th