Titlebook: Web-Age Information Management; 17th International C Bin Cui,Nan Zhang,Dexi Liu Conference proceedings 2016 Springer International Publishi

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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

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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 categorized

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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

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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

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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

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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