SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Enhanced nearest neighbour search on the R-tree
ACM SIGMOD Record
Distance browsing in spatial databases
ACM Transactions on Database Systems (TODS)
Indexing the positions of continuously moving objects
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Time-parameterized queries in spatio-temporal databases
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Continuous queries over data streams
ACM SIGMOD Record
Novel Approaches in Query Processing for Moving Object Trajectories
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Nearest Neighbor and Reverse Nearest Neighbor Queries for Moving Objects
IDEAS '02 Proceedings of the 2002 International Symposium on Database Engineering & Applications
On the Generation of Spatiotemporal Datasets
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
K-Nearest Neighbor Search for Moving Query Point
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
Spatio-Temporal Indexing for Large Multimedia Applications
ICMCS '96 Proceedings of the 1996 International Conference on Multimedia Computing and Systems
Analysis of predictive spatio-temporal queries
ACM Transactions on Database Systems (TODS)
SINA: scalable incremental processing of continuous queries in spatio-temporal databases
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Monitoring k-Nearest Neighbor Queries over Moving Objects
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
SEA-CNN: Scalable Processing of Continuous K-Nearest Neighbor Queries in Spatio-temporal Databases
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
A generic framework for monitoring continuous spatial queries over moving objects
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Conceptual partitioning: an efficient method for continuous nearest neighbor monitoring
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
R-Trees: Theory and Applications (Advanced Information and Knowledge Processing)
R-Trees: Theory and Applications (Advanced Information and Knowledge Processing)
Continuous nearest neighbor search
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Continuous K-nearest neighbor queries for continuously moving points with updates
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
HERMES: aggregative LBS via a trajectory DB engine
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Nearest Neighbor Search on Moving Object Trajectories in Secondo
SSTD '09 Proceedings of the 11th International Symposium on Advances in Spatial and Temporal Databases
Design and evaluation of trajectory join algorithms
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
BerlinMOD: a benchmark for moving object databases
The VLDB Journal — The International Journal on Very Large Data Bases
Location-dependent query processing: Where we are and where we are heading
ACM Computing Surveys (CSUR)
Efficient mutual nearest neighbor query processing for moving object trajectories
Information Sciences: an International Journal
On the effect of trajectory compression in spatiotemporal querying
ADBIS'07 Proceedings of the 11th East European conference on Advances in databases and information systems
Set nearest neighbor query for trajectory of moving objects
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 5
Constrained k-nearest neighbor query processing over moving object trajectories
DASFAA'08 Proceedings of the 13th international conference on Database systems for advanced applications
Searching trajectories by locations: an efficiency study
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Top-k queries on temporal data
The VLDB Journal — The International Journal on Very Large Data Bases
Efficient k-nearest neighbor search on moving object trajectories
The VLDB Journal — The International Journal on Very Large Data Bases
Unsupervised trajectory sampling
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
Spatiotemporal pattern queries
Geoinformatica
Pivot selection: Dimension reduction for distance-based indexing
Journal of Discrete Algorithms
Interpreting pedestrian behaviour by visualising and clustering movement data
W2GIS'13 Proceedings of the 12th international conference on Web and Wireless Geographical Information Systems
Efficient identification and approximation of k-nearest moving neighbors
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
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Nearest Neighbor (NN) search has been in the core of spatial and spatiotemporal database research during the last decade. The literature on NN query processing algorithms so far deals with either stationary or moving query points over static datasets or future (predicted) locations over a set of continuously moving points. With the increasing number of Mobile Location Services (MLS), the need for effective k-NN query processing over historical trajectory data has become the vehicle for data analysis, thus improving existing or even proposing new services. In this paper, we investigate mechanisms to perform NN search on R-tree-like structures storing historical information about moving object trajectories. The proposed (depth-first and best-first) algorithms vary with respect to the type of the query object (stationary or moving point) as well as the type of the query result (historical continuous or not), thus resulting in four types of NN queries. We also propose novel metrics to support our search ordering and pruning strategies. Using the implementation of the proposed algorithms on two members of the R-tree family for trajectory data (namely, the TB-tree and the 3D-R-tree), we demonstrate their scalability and efficiency through an extensive experimental study using large synthetic and real datasets.