Spatial query processing in an object-oriented database system
SIGMOD '86 Proceedings of the 1986 ACM SIGMOD international conference on Management of data
The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Efficient processing of spatial joins using R-trees
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Spatial joins using seeded trees
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Partition based spatial-merge join
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Incremental distance join algorithms for spatial databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Distance browsing in spatial databases
ACM Transactions on Database Systems (TODS)
Closest pair queries in spatial databases
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Indexing the positions of continuously moving objects
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Epsilon grid order: an algorithm for the similarity join on massive high-dimensional data
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
ACM Transactions on Database Systems (TODS)
Efficient aggregation over objects with extent
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Performance of multi-dimensional space-filling curves
Proceedings of the 10th ACM international symposium on Advances in geographic information systems
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
IEEE Transactions on Knowledge and Data Engineering
Proceedings of the Seventh International Conference on Data Engineering
CRB-Tree: An Efficient Indexing Scheme for Range-Aggregate Queries
ICDT '03 Proceedings of the 9th International Conference on Database Theory
Spatial Joins Using R-trees: Breadth-First Traversal with Global Optimizations
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Scalable Sweeping-Based Spatial Join
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
The R+-Tree: A Dynamic Index for Multi-Dimensional Objects
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
Supporting Incremental Join Queries on Ranked Inputs
Proceedings of the 27th International Conference on Very Large Data Bases
The X-tree: An Index Structure for High-Dimensional Data
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
A Performance Evaluation of Spatial Join Processing Strategies
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
Efficient OLAP Operations in Spatial Data Warehouses
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
Mobiscope: A Scalable Spatial Discovery Service for Mobile Network Resources
MDM '03 Proceedings of the 4th International Conference on Mobile Data Management
PISA: Performance Models for Index Structures with and without Aggregated Data
SSDBM '99 Proceedings of the 11th International Conference on Scientific and Statistical Database Management
A Non-Blocking Parallel Spatial Join Algorithm
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Range Aggregate Processing in Spatial Databases
IEEE Transactions on Knowledge and Data Engineering
Supporting top-K join queries in relational databases
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
ACM Transactions on Database Systems (TODS)
Progressive and selective merge: computing top-k with ad-hoc ranking functions
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Region clustering based evaluation of multiple top-N selection queries
Data & Knowledge Engineering
Spatial joins based on NA-trees
Information Processing Letters
Identifying the Most Endangered Objects from Spatial Datasets
SSDBM 2009 Proceedings of the 21st International Conference on Scientific and Statistical Database Management
Design and evaluation of trajectory join algorithms
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Processing top-N relational queries by learning
Journal of Intelligent Information Systems
Finding maximum degrees in hidden bipartite graphs
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
A recommendation technique for spatial data
ADBIS'11 Proceedings of the 15th international conference on Advances in databases and information systems
Topological operators: a relaxed query processing approach
Geoinformatica
Evaluation of top-k OLAP queries using aggregate r–trees
SSTD'05 Proceedings of the 9th international conference on Advances in Spatial and Temporal Databases
Exact and approximate algorithms for the most connected vertex problem
ACM Transactions on Database Systems (TODS)
Efficient top-k spatial distance joins
SSTD'13 Proceedings of the 13th international conference on Advances in Spatial and Temporal Databases
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Given two spatial data sets A and B, a top-k spatial join retrieves the k objects from A or B that intersect the largest number of objects from the other data set. Depending on the application requirements, there exist several variations of the problem. For instance, B may be a point data set, and the goal may be to retrieve the regions of A that contain the maximum number of points. The processing of such queries with conventional spatial join algorithms is expensive. However, several improvements are possible based on the fact that we only require a small subset of the result (instead of all intersection/containments pairs). In this paper, we propose output-sensitive algorithms for top-k spatial joins that utilize a variety of optimizations for reducing the overhead.