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Foundations of Multidimensional and Metric Data Structures The Morgan Kaufmann Series in Data Management Systems Series

Langue : Anglais

Auteur :

Couverture de l’ouvrage Foundations of Multidimensional and Metric Data Structures

Foundations of Multidimensional and Metric Data Structures provides a thorough treatment of multidimensional point data, object and image-based representations, intervals and small rectangles, and high-dimensional datasets.

The book includes a thorough introduction; a comprehensive survey to spatial and multidimensional data structures and algorithms; and implementation details for the most useful data structures. Each section includes a large number of exercises and solutions to self-test and confirm the reader's understanding and suggest future directions.

The book is an excellent and valuable reference tool for professionals in many areas, including computer graphics, databases, geographic information systems (GIS), game programming, image processing, pattern recognition, solid modeling, similarity retrieval, and VLSI design.

Multidimensional data is data that exists and changes in more than one dimension, by time, or spatially, or both, sometimes dynamically. Think here of tracking hurricane data in order to project the storm's path, for just one example. As spatial and other multidimensional data structures become increasingly important for the applications in game programming, data mining, bioinformatics, and many other areas--including astronomy, geographic information systems, physics, etc., the need for a comprehensive book on the subject is paramount. This book is truly a life's work by the author who is clearly the best person for the job.
This book is for the use of computer scientists who have a need to represent spatial data and as such will appeal to those in data management, computer graphics, game programming, bioinformatics, pattern recognition, GIS, and other non-CS fields like high energy physics, geography, mathematics, and engineering.
Hanan Samet is Professor in the Department of Computer Science at the University of Maryland, and a member of the Center for Automation Research and the Institute for Advanced Computer Studies. He is widely published in the fields of spatial databases and data structures, computer graphics, image databases and image processing, and geographic information systems (GIS), and is considered an authority on the use and design of hierarchical spatial data structures such as the quadtree and octree for geographic information systems, image processing, and computer graphics. He is the author of the two books The Design and Analysis of Spatial Data Structures and Applications of Spatial Data Structures: Computer Graphics, Image Processing and GIS. He holds a Ph.D. in computer science from Stanford University.
  • First comprehensive work on multidimensional data structures available, a thorough and authoritative treatment
  • An algorithmic rather than mathematical approach, with a liberal use of examples that allows the readers to easily see the possible implementation and use
  • Each section includes a large number of exercises and solutions to self-test and confirm the reader's understanding and suggest future directions
  • Written by a well-known authority in the area of spatial data structures who has made many significant contributions to the field
  • The author's website includes: Spatial Index Demos

Date de parution :

Ouvrage de 1024 p.

21.5x27.6 cm

Sous réserve de disponibilité chez l'éditeur.

76,17 €

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