Description

Book Synopsis
Discusses multidimensional point data, object and image-based representations, intervals and small rectangles, and high-dimensional datasets. This book includes a comprehensive survey to spatial and multidimensional data structures and algorithms. It also includes implementation details for some of the most useful data structures.

Trade Review
Honorable Mention Award in the 2006 best book in Computer and Information Science competition from the Professional and Scholarly Publishers(PSP) Group of the American Publishers Association (AAP) “Hanan Samet is the dean of “spatial indexing”... This book is encyclopedic... this book will be invaluable for those of us who struggle with spatial data, scientific datasets, graphics, vision problems involving volumetric queries, or with higher dimensional datasets common in data mining.” —From the foreword by Jim Gray, Microsoft Research “Samet’s book on multidimensional and metric data structures is the most complete and thorough presentation on this topic. It has broad coverage of material from computational geometry, databases, graphics, GIS, and similarity retrieval literature. Written by the leading authority on hierarchical spatial representations, this book is a “must have” for all instructors, researchers, and developers working and teaching in these areas.” —Dinesh Manocha, University of North Carolina at Chapel Hill “To summarize, this book is excellent! It’s a very comprehensive survey of spatial and multidimensional data structures and algorithms, which is badly needed. The breadth and depth of coverage is astounding and I would consider several parts of it required reading for real time graphics and game developers.” —Bretton Wade, University of Washington and Microsoft Corp. “It’s a truly encyclopedic book on data structures for accelerating all sorts of 3D queries.” —Hector Yee, Hectorgon – A Graphics Programming Blog, October 18, 2006

Table of Contents
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.

Foundations of Multidimensional and Metric Data

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    A Hardback by Hanan Samet

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      View other formats and editions of Foundations of Multidimensional and Metric Data by Hanan Samet

      Publisher: Elsevier Science
      Publication Date: 9/12/2006 12:00:00 AM
      ISBN13: 9780123694461, 978-0123694461
      ISBN10: 0123694469

      Description

      Book Synopsis
      Discusses multidimensional point data, object and image-based representations, intervals and small rectangles, and high-dimensional datasets. This book includes a comprehensive survey to spatial and multidimensional data structures and algorithms. It also includes implementation details for some of the most useful data structures.

      Trade Review
      Honorable Mention Award in the 2006 best book in Computer and Information Science competition from the Professional and Scholarly Publishers(PSP) Group of the American Publishers Association (AAP) “Hanan Samet is the dean of “spatial indexing”... This book is encyclopedic... this book will be invaluable for those of us who struggle with spatial data, scientific datasets, graphics, vision problems involving volumetric queries, or with higher dimensional datasets common in data mining.” —From the foreword by Jim Gray, Microsoft Research “Samet’s book on multidimensional and metric data structures is the most complete and thorough presentation on this topic. It has broad coverage of material from computational geometry, databases, graphics, GIS, and similarity retrieval literature. Written by the leading authority on hierarchical spatial representations, this book is a “must have” for all instructors, researchers, and developers working and teaching in these areas.” —Dinesh Manocha, University of North Carolina at Chapel Hill “To summarize, this book is excellent! It’s a very comprehensive survey of spatial and multidimensional data structures and algorithms, which is badly needed. The breadth and depth of coverage is astounding and I would consider several parts of it required reading for real time graphics and game developers.” —Bretton Wade, University of Washington and Microsoft Corp. “It’s a truly encyclopedic book on data structures for accelerating all sorts of 3D queries.” —Hector Yee, Hectorgon – A Graphics Programming Blog, October 18, 2006

      Table of Contents
      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.

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