Influence sets based on reverse nearest neighbor queries
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
An Index Structure for Efficient Reverse Nearest Neighbor Queries
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GIS '03 Proceedings of the 11th ACM international symposium on Advances in geographic information systems
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SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
In-Route Nearest Neighbor Queries
Geoinformatica
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VLDB '05 Proceedings of the 31st international conference on Very large data bases
On computing top-t most influential spatial sites
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Reverse Nearest Neighbors in Large Graphs
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The VLDB Journal — The International Journal on Very Large Data Bases
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SSDBM '06 Proceedings of the 18th International Conference on Scientific and Statistical Database Management
Reverse kNN search in arbitrary dimensionality
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
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VLDB '07 Proceedings of the 33rd international conference on Very large data bases
FINCH: evaluating reverse k-Nearest-Neighbor queries on location data
Proceedings of the VLDB Endowment
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Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
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Efficient method for maximizing bichromatic reverse nearest neighbor
Proceedings of the VLDB Endowment
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Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
Influence zone: Efficiently processing reverse k nearest neighbors queries
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
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In this paper, we propose and investigate a novel spatial query called Reverse Path Nearest Neighbor (R-PNN) search to find the most accessible locations in road networks. Given a trajectory data-set and a list of location candidates specified by users, if a location o is the Path Nearest Neighbor (PNN) of k trajectories, the influence-factor of o is defined as k and the R-PNN query returns the location with the highest influence-factor. The R-PNN query is an extension of the conventional Reverse Nearest Neighbor (RNN) search. It can be found in many important applications such as urban planning, facility allocation, traffic monitoring, etc. To answer the R-PNN query efficiently, an effective trajectory data pre-processing technique is conducted in the first place. We cluster the trajectories into several groups according to their distribution. Based on the grouped trajectory data, a two-phase solution is applied. First, we specify a tight search range over the trajectory and location data-sets. The efficiency study reveals that our approach defines the minimum search area. Second, a series of optimization techniques are adopted to search the exact PNN for trajectories in the candidate set. By combining the PNN query results, we can retrieve the most accessible locations. The complexity analysis shows that our solution is optimal in terms of time cost. The performance of the proposed R-PNN query processing is verified by extensive experiments based on real and synthetic trajectory data in road networks.