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Efficient k-Closest-Pair Range-Queries in Spatial Databases

2008
*
2008 The Ninth International Conference on Web-Age Information Management
*

*In*order to efficiently retrieve

*the*

*k*

*closest*

*pairs*between two

*spatial*data

*sets*

*in*a specified space, such as

*in*GIS and CAD applications, we propose a novel algorithm to handle

*the*

*k*-

*closest*-

*pair*range-query ...

*In*particular, this technique works well

*when*two

*spatial*data

*sets*are identical.

*The*Ninth International Conference

*on*Web-Age Information Management 978-0-7695-3185-4/08 $25.00 ...

*One*important

*spatial*

*database*query

*is*called "

*k*

*Closest*

*Pairs*Query" (

*k*-CPQ), which combines join and nearest neighbor queries

*in*order to find

*the*

*closest*

*k*

*pairs*of

*spatial*objects from two distinct ...

##
###
Processing Constrained k-Closest Pairs Queries in Crime Databases
[chapter]

2009
*
Annals of Information Systems
*

called Growing Window based Constrained

doi:10.1007/978-1-4419-1325-8_4
fatcat:ttqp3gecxjfdfme65qqpxnb7iu
*k*-*Closest**Pairs*(GWCCP). ... Recently,*spatial*analysis*in*crime*databases*has attracted increased attention. ...*The*problem of "*k*-*Closest**Pairs*Query" (*k*-CPQ)*is*an extension by combining nearest neighbor query with*spatial*join*in*order to find*the**k*-*closest**pairs*of*spatial*objects from two distinct data*sets*...##
###
On Spatial-Range Closest-Pair Query
[chapter]

2003
*
Lecture Notes in Computer Science
*

An important query for

doi:10.1007/978-3-540-45072-6_15
fatcat:qkgyndzfonhilleqo6cmpri654
*spatial**database*research*is*to find*the**closest**pair*of objects*in*a given space. ... Existing work assumes two objects of*the**closest**pair*come from two different data*sets**indexed*by R-trees.*The**closest**pair**in**the*whole space will be found via an optimzed R-tree join technique. ...*One*important*spatial**database*query*is**the**closest**pair*(CP) query, which*is*to find*the**closest**pair*of objects among two data*sets*. ...##
###
Enhancing SpatialHadoop with Closest Pair Queries
[chapter]

2016
*
Lecture Notes in Computer Science
*

Given two datasets P and Q,

doi:10.1007/978-3-319-44039-2_15
fatcat:ny5fte4l35g4ppjmqtfln25kqe
*the**K**Closest**Pair*Query (KCPQ) finds*the**K**closest**pairs*of objects from P ×Q. It*is*an operation widely adopted by many*spatial*and GIS applications. ... As a combination of*the**K*Nearest Neighbor (KNN) and*the**spatial*join queries, KCPQ*is*an expensive operation. ... X)*in*increasing order, and (2) combine*one*point (pivot) of*one**set*with all*the*points of*the*other*set*satisfying point.x − pivot.x ≤ δ, where δ*is**the*distance of*the**K*-th*closest**pair*found so far ...##
###
Closest Pair Queries with Spatial Constraints
[chapter]

2005
*
Lecture Notes in Computer Science
*

An extension to this problem

doi:10.1007/11573036_1
fatcat:uqos5wuburcq3aj4krvmo3676u
*is*to generate*the**k**closest**pairs*of objects (*k*-CPQ). ...*In*this work we focus*on*constrained*closest*-*pair*queries (CCPQ), between two distinct datasets D A and D B , where objects from DA must be enclosed by a*spatial*region R. ...*In*this study, we focus*on**the**k*-Semi-*Closest*-*Pair*Query (*k*-SCPQ), and more specifically,*on*an interesting variation which*is*derived by applying*spatial*constraints*in**the*objects of*the*first dataset ...##
###
Spatial Queries in the Presence of Obstacles
[chapter]

2004
*
Lecture Notes in Computer Science
*

Despite

doi:10.1007/978-3-540-24741-8_22
fatcat:fw53ai3dgzexnnsgrnj3zjtt4a
*the*existence of obstacles*in*many*database*applications, traditional*spatial*query processing utilizes*the*Euclidean distance metric assuming that points*in*space are directly reachable. ... We propose efficient algorithms for*the*most important query types, namely, range search, nearest neighbors, e-distance joins and*closest**pairs*, considering that both data objects and obstacles are*indexed*... Several*spatial*join algorithms have been proposed for*the*case where*only**one*of*the*inputs*is**indexed*by an R-tree or no input*is**indexed*. ...##
###
Query Processing in Spatial Network Databases
[chapter]

2003
*
Proceedings 2003 VLDB Conference
*

These frameworks are successfully applied to

doi:10.1016/b978-012722442-8/50076-8
dblp:conf/vldb/PapadiasZMT03
fatcat:ai2px5dttvhxfdtfc55tos7pyq
*the*most popular*spatial*queries, namely nearest neighbors, range search,*closest**pairs*and edistance joins,*in**the*context of*spatial*network*databases*. ... Despite*the*importance of*spatial*networks*in*real-life applications, most of*the**spatial**database*literature focuses*on*Euclidean spaces. ... We would like to thank Qiongmao Shen and Manli Zhu for helping with*the*implementation. ...##
###
Supporting KDD Applications by the k-Nearest Neighbor Join
[chapter]

2003
*
Lecture Notes in Computer Science
*

to a

doi:10.1007/978-3-540-45227-0_50
fatcat:x76wu4j6ijcwhgx6e2cncsz42i
*k*-*closest**pair*operation*in*computational geometry, cf. [19] ). ...*In*this paper, we propose an important, third similarity join operation called*k*-nearest neighbor join which combines each point of*one*point*set*with its*k*nearest neighbors*in**the*other*set*. ... Most related work*on*join processing using multidimensional*index*structures*is*based*on**the**spatial*join. ...##
###
The k-Nearest Neighbour Join: Turbo Charging the KDD Process

2004
*
Knowledge and Information Systems
*

*In*this paper, we propose an important, third similarity join operation called

*k*-nearest neighbor join which combines each point of

*one*point

*set*with its

*k*nearest neighbors

*in*

*the*other

*set*. ... A similarity join combines two

*sets*of complex objects such that

*the*result contains all

*pairs*of similar objects. ... Most related work

*on*join processing using multidimensional

*index*structures

*is*based

*on*

*the*

*spatial*join. ...

##
###
Query processing in spatial databases containing obstacles

2005
*
International Journal of Geographical Information Science
*

Despite

doi:10.1080/13658810500286935
fatcat:f5g74lqz2zcshnvvvhaeqwac5i
*the*existence of obstacles*in*many*database*applications, traditional*spatial*query processing assumes that points*in*space are directly reachable and utilizes*the*Euclidean distance metric. ...*In*this paper, we study*spatial*queries*in**the*presence of obstacles, where*the*obstructed distance between two points*is*defined as*the*length of*the*shortest path that connects them without crossing ... Acknowledgements This research was supported by*the*grant HKUST 6178/04E from Hong Kong RGC and*the*grant RGg/05 form NTU URC/AcRF. ...##
###
A Comparison of Distributed Spatial Data Management Systems for Processing Distance Join Queries
[chapter]

2017
*
Lecture Notes in Computer Science
*

Two of

doi:10.1007/978-3-319-66917-5_15
fatcat:7luj3dj4kvfbdf45sqxsxdpvu4
*the*most studied distance join queries are*the**K**Closest**Pair*Query (KCPQ) and*the*ε Distance Join Query (εDJQ). ...*The*KCPQ finds*the**K**closest**pairs*of points from two datasets and*the*εDJQ finds all*the*possible*pairs*of points from two datasets, that are within a distance threshold ε of each other. ... value of*the**K*-th*closest**pair*(β). ...##
###
New plane-sweep algorithms for distance-based join queries in spatial databases

2016
*
Geoinformatica
*

*The*most representative and studied DJQs are

*the*

*K*

*Closest*

*Pairs*Query (KCPQ) and εDistance Join Query (εDJQ). ... These

*spatial*queries involve two

*spatial*data

*sets*and a distance function to measure

*the*degree of closeness, along with a given number of

*pairs*

*in*

*the*final result (

*K*) or a distance threshold (ε). ... Acknowledgements Work of all authors funded by

*the*Development of a GeoENvironmental information system for

*the*region of CENtral Greece (GENCENG) project (SYN-ERGASIA 2011 action, supported by

*the*European ...

##
###
Efficient large-scale distance-based join queries in spatialhadoop

2017
*
Geoinformatica
*

*The*most representative and known DBJQs are

*the*

*K*

*Closest*

*Pairs*Query (KCPQ) and

*the*ε Distance Join Query (εDJQ). ... Efficient processing of Distance-Based Join Queries (DBJQs)

*in*

*spatial*

*databases*

*is*of paramount importance

*in*many application domains. ...

*K*

*Closest*

*Pairs*Query

*The*KCPQ discovers

*the*

*K*

*pairs*of data formed from

*the*elements of two datasets having

*the*

*K*smallest respective distances between them (i.e. it reports

*only*

*the*top

*K*

*pairs*). ...

##
###
Multi-Way Distance Join Queries in Spatial Databases

2004
*
Geoinformatica
*

This query can be viewed as an extension of

doi:10.1023/b:gein.0000040832.25622.8d
fatcat:3vbnkdhaubebxekdy67bubuu4i
*K*-*Closest*-*Pairs*Query (*K*-CPQ) [CMT + 01] for n inputs. ... This paper addresses*the*problem of finding*the**K*n-tuples between n*spatial*datasets that have*the*smallest D distance -values,*the*so-called*K*-Multi-Way Distance Join Query (*K*-MWDJQ), where each*set*... to consider as related work*the*cases where*only**one*of*the*inputs*is**indexed*[LoR94, PRS99, MaP03] or*when*both inputs are non-*indexed*[LoR96, PaD96, KoS97] . ...##
###
Processing Distance Join Queries with Constraints

2005
*
Computer journal
*

An extension to this problem

doi:10.1093/comjnl/bxl002
fatcat:iu6fjwgiwzafnfoqwbq7sd4mbi
*is*to generate*the**k**closest**pairs*of objects (*k*-CPQ). ...*In*this work, we focus*on*constrained*closest*-*pair*queries, between two distinct datasets D A and D B , where objects from D A must be enclosed by a*spatial*region R. ... Given two*spatial*datasets D A and D B and a predicate ,*the*output of*the**spatial*join query*is*a*set*of*pairs*o a , o b such that o a 2 D A , o b 2 D B and (o a , o b )*is*true.*k**Closest*-*pair*query ...
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