Publications

Samet, 2006/1024pp/Hardcover, ISBN: 0-12-369446-9

Here, for the first time, is a thorough treatment of multidimensional point data, object and image-based representations, intervals and small rectangles, and high-dimensional and metric datasets, including many novel methods not available elsewhere.

Coverage of particular interest to data mining and knowledge discovery includes:

1. Exhaustive nearest neighbor finding treatment 2. Distance-based indexing methods 3. SASH: Indexing without the triangle inequality 4. Locality Sensitive Hashing (LSH) 5. Embedding methods 6. Dimension reduction methods

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. Along with the hundreds of worked exercises and hundreds of illustrations, the result is an excellent and valuable reference tool for professionals in many areas, including computer graphics, databases, geographic information systems (GIS) and spatial databases, game programming, image processing and computer vision, pattern recognition, solid modeling and computational geometry, similarity retrieval, VLSI design, and search aspects of bioinformatics

Critical Acclaim for Foundations of Multidimensional and Metric Data Structures:

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, or scientific datasets, or with graphics, and vision problems involving volumetric queries, or with higher dimensional datasets common in data mining.
  From the foreword by Jim Gray, Microsoft Research

For complete table of contents and more information, Downloadable pdf of sample pages from the book, and to order, visit: http://www.mkp.com/multidimensional

This book is available for purchase on www.amazon.com and all fine bookstores.

Morgan Kaufmann Publishers
www.mkp.com