Identifying the Most Endangered Objects from Spatial Datasets
SSDBM 2009 Proceedings of the 21st International Conference on Scientific and Statistical Database Management
Skyline queries based on user locations and preferences for making location-based recommendations
Proceedings of the 2009 International Workshop on Location Based Social Networks
Z-SKY: an efficient skyline query processing framework based on Z-order
The VLDB Journal — The International Journal on Very Large Data Bases
Direction-based spatial skylines
Proceedings of the Ninth ACM International Workshop on Data Engineering for Wireless and Mobile Access
Efficient evaluation of location-dependent skyline queries using non-dominance scopes
Proceedings of the 2nd International Conference on Computing for Geospatial Research & Applications
Direction-based surrounder queries for mobile recommendations
The VLDB Journal — The International Journal on Very Large Data Bases
Authentication of location-based skyline queries
Proceedings of the 20th ACM international conference on Information and knowledge management
Optimized skyline queries on road networks using nearest neighbors
Personal and Ubiquitous Computing
Combining top-k query in road networks
WAIM'11 Proceedings of the 2011 international conference on Web-Age Information Management
Complex preference queries supporting spatial applications for user groups
Proceedings of the VLDB Endowment
| Hi-index | 0.00 |
Given a set of data points with both spatial coordinates andnon-spatial attributes, point a location-dependently dominates point b with respect to a query point q if a is closer to q than b and meanwhile a dominates b. A location-dependent skyline query (LDSQ) issued at point q is to retrieve all the points that are not location-dependently dominated by other points with regard to q. In this paper, we focus on the query processing and result validation of LDSQ overstatic objects. Two algorithms, namely brute-forth and δ-scanning, are proposed. The former serves as the baseline algorithm while the latter significantly improves the performance via space pruning. We further conduct a comprehensive simulation to demonstrate the performance of proposed algorithms.