Influence sets based on reverse nearest neighbor queries
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
An Index Structure for Efficient Reverse Nearest Neighbor Queries
Proceedings of the 17th International Conference on Data Engineering
Efficient Processing of Spatial Queries in Line Segment Databases
SSD '91 Proceedings of the Second International Symposium on Advances in Spatial Databases
Reverse Nearest Neighbors in Large Graphs
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Reverse Nearest Neighbors in Large Graphs
IEEE Transactions on Knowledge and Data Engineering
Reverse Nearest Neighbors Search in Ad-hoc Subspaces
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Continuous Reverse Nearest Neighbor Monitoring
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Continuous nearest neighbor monitoring in road networks
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Distance indexing on road networks
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Reverse kNN search in arbitrary dimensionality
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Scalable network distance browsing in spatial databases
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Ranked Reverse Nearest Neighbor Search
IEEE Transactions on Knowledge and Data Engineering
Continuous Reverse k-Nearest-Neighbor Monitoring
MDM '08 Proceedings of the The Ninth International Conference on Mobile Data Management
Hierarchical Graph Embedding for Efficient Query Processing in Very Large Traffic Networks
SSDBM '08 Proceedings of the 20th international conference on Scientific and Statistical Database Management
Continuous Reverse Nearest Neighbor Queries on Moving Objects in Road Networks
WAIM '08 Proceedings of the 2008 The Ninth International Conference on Web-Age Information Management
Reverse k-nearest neighbor search in dynamic and general metric databases
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Continuous K-Nearest Neighbor Query over Moving Objects in Road Networks
APWeb/WAIM '09 Proceedings of the Joint International Conferences on Advances in Data and Web Management
Visible Reverse k-Nearest Neighbor Queries
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Distance Oracles for Spatial Networks
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Reverse k Nearest Neighbor and Reverse Farthest Neighbor Search on Spatial Networks
Transactions on Large-Scale Data- and Knowledge-Centered Systems I
Probabilistic Reverse Nearest Neighbor Queries on Uncertain Data
IEEE Transactions on Knowledge and Data Engineering
Optimizing predictive queries on moving objects under road-network constraints
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part I
Efficiently processing snapshot and continuous reverse k nearest neighbors queries
The VLDB Journal — The International Journal on Very Large Data Bases
Predictive line queries for traffic prediction
Transactions on Large-Scale Data- and Knowledge-Centered Systems VI
Searching continuous nearest neighbors in road networks on the air
Information Systems
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Continuous reverse k nearest neighbor (CRkNN) monitoring in road networks has recently received increasing attentions. However, there is still a lack of efficient CRkNN algorithms in road networks up to now. In road networks, moving query objects and data objects are restricted by the connectivity of the road network and both the object-query distance and object-object distance updates affect the result of CRkNN queries. In this paper, we present a novel algorithm for continuous and incremental evaluation of CRkNN queries in road networks. Our method is based on a novel data structure called dual layer multiway tree (DLM tree) we proposed to represent the whole monitoring region of a CRkNN query q. We propose several lemmas to reduce the monitoring region of q and the number of candidate objects as much as possible. Moreover, by associating a variable NN_count with each candidate object, we can simplify the monitoring of candidate objects. There are a large number of objects roaming in a road network and many of them are irrelevant to a specific CRkNN query of a query object q. To minimize the processing extension, for a road in the network, we give an IQL list and an IQCL list to specify the set of query objects and data objects whose location updates should be maintained for CRkNN processing of query objects. Our CRkNN method consists of two phase: the initial result generating phase and incremental maintenance phase. In each phase, algorithms with high performance are proposed to make our CRkNN method more efficient. Extensive simulation experiments are conducted and the result shows that our proposed approach is efficient and scalable in processing CRkNN queries in road networks.