• Sign In
  • Help
  • My Basket0
Similarity Search in High-Dimensional Vector Spaces - Dissertations in Database and Information Systems v. 74 (Paperback)
  • Similarity Search in High-Dimensional Vector Spaces - Dissertations in Database and Information Systems v. 74 (Paperback)
zoom

Similarity Search in High-Dimensional Vector Spaces - Dissertations in Database and Information Systems v. 74 (Paperback)

(author)
£27.00
Paperback 240 Pages / Published: 01/01/2001
  • Not available

This product is currently unavailable.

  • This item has been added to your basket

Check Marketplace availability

This dissertation addresses the problem of identifying the most similar objects in a database given a set of reference objects and a set of features. It investigates the so-called "Curse of Dimensionality", and presents an organization for NN-Search ("Nearest Neighbour Search") optimized for high-dimensional spaces - the so-called "Vector Approximation File" (VA-File). The text shows the superiority of the VA-File theoretically and through experiments. The VA-File is also discussed with reference to approximate search and parallel search in a cluster of workstations. This dissertaion also provides an indexing technique that allows for interactive-time similarity search even in huge databases.

Publisher: IOS Press
ISBN: 9781586031770
Number of pages: 240

You may also be interested in...

Access 2013 All-In-One for Dummies
Added to basket
PHP and MySQL Web Development
Added to basket
Data Science for Business
Added to basket
Principles of Data Management
Added to basket
Big Data For Dummies
Added to basket
Practical Data Science with R
Added to basket
Doing Data Science
Added to basket
£35.99
Paperback
Hadoop - The Definitive Guide 4e
Added to basket
SQL Queries for Mere Mortals
Added to basket
Agile Data Warehouse Design
Added to basket
Data Wrangling with Python
Added to basket
Learning Spark
Added to basket
£31.99
Paperback
Designing Data-Intensive Applications
Added to basket

Reviews

Please sign in to write a review

Your review has been submitted successfully.