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Algorithms for Spatial Data Integration

  • Mark McKenneyEmail author
Chapter

Abstract

The map construction problem (MCP) is defined as a spatial data integration problem relating to the integration of region data into map data. Although a purely geometric integration of regions into a map is known and is efficient, algorithms preserving thematic data of regions are much more difficult. A naive approach to the MCP runs in O((nmlgnm)2+k) time for m regions composed with n line segments on average with k line segment intersections. A new \(O((n + k)(\lg n + m +\lg {m}^{2}))\) algorithm is presented to solve the MCP. The algorithm has been implemented and experiments show that it is significantly faster than the naive approach, but is prone to large memory usage when run over large data sets. An external memory version of the algorithm is presented that is efficient for very large data sets, and requires significantly less memory than the original algorithm.

Keywords

Data Item External Memory Active List Input Region Binary Search Tree 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Vienna 2012

Authors and Affiliations

  1. 1.Department of Computer ScienceTexas State UniversitySan MarcosUSA

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