A Taxonomy for Distance-Based Spatial Join Queries
Lingxiao Li and
David Taniar
Additional contact information
Lingxiao Li: Monash University, Melbourne, Australia
David Taniar: Monash University, Melbourne, Australia
International Journal of Data Warehousing and Mining (IJDWM), 2017, vol. 13, issue 3, 1-24
Abstract:
Join operation is one of the most used operations in database management systems, including spatial databases. Hence, spatial join queries are very important in spatial database processing. There are many different kinds of spatial join queries, due to the richness in spatial data types and spatial operations. Therefore, it is important to understand the full spectrum of spatial join queries. The aim of this paper is to give a classification to one family type of spatial join, called the Distance-based Spatial Join. In the taxonomy, the authors divide this spatial join into three categories: (i) AllRange, (ii) All-kNN, and (iii) All-RNN. Each of these categories has its own variants. In this taxonomy, the authors confine the discussions to join queries on fixed points.
Date: 2017
References: Add references at CitEc
Citations:
Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 018/IJDWM.2017070101 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:igg:jdwm00:v:13:y:2017:i:3:p:1-24
Access Statistics for this article
International Journal of Data Warehousing and Mining (IJDWM) is currently edited by Eric Pardede
More articles in International Journal of Data Warehousing and Mining (IJDWM) from IGI Global
Bibliographic data for series maintained by Journal Editor ().