Principles of database buffer management
ACM Transactions on Database Systems (TODS)
Computational geometry: an introduction
Computational geometry: an introduction
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
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
Multidimensional access methods
ACM Computing Surveys (CSUR)
Enhanced nearest neighbour search on the R-tree
ACM SIGMOD Record
An optimal algorithm for approximate nearest neighbor searching fixed dimensions
Journal of the ACM (JACM)
Processing and optimization of multiway spatial joins using R-trees
PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
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
Adaptive multi-stage distance join processing
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
An Algorithm for Finding Best Matches in Logarithmic Expected Time
ACM Transactions on Mathematical Software (TOMS)
ACM Computing Surveys (CSUR)
Object-Relational Database Development: A Plumber's Guide with Cdrom
Object-Relational Database Development: A Plumber's Guide with Cdrom
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Cost Models for Join Queries in Spatial Databases
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Performance of Nearest Neighbor Queries in R-Trees
ICDT '97 Proceedings of the 6th 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
The R+-Tree: A Dynamic Index for Multi-Dimensional Objects
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
Extensible Buffer Management of Indexes
VLDB '92 Proceedings of the 18th International Conference on Very Large Data Bases
SSD '95 Proceedings of the 4th International Symposium on Advances in Spatial Databases
Multi-Way Distance Join Queries in Spatial Databases
Geoinformatica
An approximate algorithm for top-k closest pairs join query in large high dimensional data
Data & Knowledge Engineering
Cost models for distance joins queries using R-trees
Data & Knowledge Engineering
Exploiting a page-level upper bound for multi-type nearest neighbor queries
GIS '06 Proceedings of the 14th annual ACM international symposium on Advances in geographic information systems
A performance comparison of distance-based query algorithms using R-trees in spatial databases
Information Sciences: an International Journal
Efficient k-nearest-neighbor search algorthims for historical moving object trajectories
Journal of Computer Science and Technology
Reversible Data Hiding in the VQ-Compressed Domain
IEICE - Transactions on Information and Systems
On efficient mutual nearest neighbor query processing in spatial databases
Data & Knowledge Engineering
PDA: A Flexible and Efficient Personal Decision Assistant
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
Proceedings of the VLDB Endowment
Join-queries between two spatial datasets indexed by a single R*-tree
SOFSEM'11 Proceedings of the 37th international conference on Current trends in theory and practice of computer science
Finding the k-closest pairs in metric spaces
Proceedings of the 1st Workshop on New Trends in Similarity Search
Proximity rank join in search computing
Search computing
Top-K probabilistic closest pairs query in uncertain spatial databases
APWeb'11 Proceedings of the 13th Asia-Pacific web conference on Web technologies and applications
Finding the sites with best accessibilities to amenities
DASFAA'11 Proceedings of the 16th international conference on Database systems for advanced applications: Part II
Evaluating probabilistic spatial-range closest pairs queries over uncertain objects
WAIM'11 Proceedings of the 12th international conference on Web-age information management
Closest pair queries with spatial constraints
PCI'05 Proceedings of the 10th Panhellenic conference on Advances in Informatics
Proximity measures for rank join
ACM Transactions on Database Systems (TODS)
VA-files vs. r*-trees in distance join queries
ADBIS'05 Proceedings of the 9th East European conference on Advances in Databases and Information Systems
SSDBM'12 Proceedings of the 24th international conference on Scientific and Statistical Database Management
The k closest pairs in spatial databases
Geoinformatica
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This paper addresses the problem of finding the K closest pairs between two spatial datasets (the so-called, K closest pairs query, K-CPQ), where each dataset is stored in an R-tree. There are two different techniques for solving this kind of distance-based query. The first technique is the incremental approach, which returns the output elements one-by-one in ascending order of distance. The second one is the nonincremental alternative, which returns the K elements of the result all together at the end of the algorithm. In this paper, based on distance functions between two MBRs in the multidimensional Euclidean space, we propose a pruning heuristic and two updating strategies for minimizing the pruning distance, and use them in the design of three non-incremental branch-and-bound algorithms for K-CPQ between spatial objects stored in two R-trees. Two of those approaches are recursive following a Depth-First searching strategy and one is iterative obeying a Best-First traversal policy. The plane-sweep method and the search ordering are used as optimization techniques for improving the naive approaches. Besides, a number of interesting extensions of the K-CPQ (K-Self-CPQ, Semi-CPQ, K-FPQ (the K-farthest pairs query), etc.) are discussed. An extensive performance study is also presented. This study is based on experiments performed with real datasets. A wide range of values for the basic parameters affecting the performance of the algorithms is examined in order to designate the most efficient algorithm for each setting of parameter values. Finally, an experimental study of the behavior of the proposed K-CPQ branch-and-bound algorithms in terms of scalability of the dataset size and the K value is also included.