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Understanding High-Dimensional Spaces

High-dimensional spaces arise as a way of modelling datasets with many attributes. Such a dataset can be directly represented in a space spanned by its attributes, with each record represented as a point in the space with its position depending on its attribute values. Such spaces are not easy to wo...

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Bibliographic Details
Main Author: Skillicorn, David B.
Format: eBook
Language:English
Published: Berlin, Heidelberg Springer Berlin Heidelberg 2012, 2012
Edition:1st ed. 2012
Series:SpringerBriefs in Computer Science
Subjects:
Computer Communication Networks
Electronic Commerce
Artificial Intelligence
Data Structures And Information Theory
Computer Networks 
Information Theory
Data Protection
Data Structures (computer Science)
E-commerce And E-business
Data And Information Security
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • Introduction
  • Basic Structure of High-Dimensional Spaces
  • Algorithms
  • Spaces with a Single Center
  • Spaces with Multiple Clusters
  • Representation by Graphs
  • Using Models of High-Dimensional Spaces
  • Including Contextual Information
  • Conclusions
  • Index
  • References

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