Finding the best ranking model for spatial objects

Abstract

Top-k spatial preference queries has a wide range of applications in service recommendation and decision support systems. In this work we first introduce three state of the art algorithms and apply them on a real data set which includes geographic coordinates and quality data of over 355 hotels, 276 point of interests and 563 restaurants in Lisbon, Portugal extracted from well-known TripAdvisor2. This is the first time that mentioned algorithms are evaluated on a real data set. We also use some optimization tasks for the estimation of algorithms parameters. Finally we rank the hotels using the best obtained ranking model. Result reveals that influence score with a particular radius is able to rank spatial objects very near to the real rankings.