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What is Filter-Refine Paradigm

Chapter 30
Handbook of Research on Innovations in Database Technologies and Applications: Current and Future Trends
Algorithms that follow this paradigm are two-step algorithms. Filter step: an approximation of each spatial object is used to produce a set of candidates (and, possibly, a set of actual answers), which is a superset of the answer set consisting of actual answers and false hits. Refinement step: each candidate from the filter step is then examined with respect to its exact geometry in order to produce the answer set by eliminating false hits.
Published in Chapter:
Query Processing in Spatial Databases
Antonio Corral (University of Almeria, Spain) and Michael Vassilakopoulos (University of Central Greece, Greece)
Copyright: © 2009 |Pages: 10
DOI: 10.4018/978-1-60566-242-8.ch030
Abstract
Spatial data management has been an active area of intensive research for more than two decades. In order to support spatial objects in a database system several important issues must be taken into account such as: spatial data models, indexing mechanisms and efficient query processing. A spatial database system (SDBS) is a database system that offers spatial data types in its data model and query language and supports spatial data types in its implementation, providing at least spatial indexing and efficient spatial query processing (Güting, 1994). The main reason that has caused the active study of spatial database management systems (SDBMS) comes from the needs of the existing applications such as geographical information systems (GIS), computer-aided design (CAD), very large scale integration design (VLSI), multimedia information systems (MIS), data warehousing, multi-criteria decision making, location-based services, etc.
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