Associative Data Access Method (ADAM).

Abstract

A software solution to the multikey access problem is presented. The result, ADAM, models associative memory techniques to obtain fast retrieval times and efficient data storage. A multidimensional tree structure is used. Each data item key is one dimension, and at each lower level in the tree each dimension is divided into successively smaller half-intervals. Unlike m-way trees with fixed sized nodes and K-D tree levels, each ADAM map level is a linear linked list. Each node of the ADAM level linear linked list is the root of a subtree, or is the terminal node of a data item in the data set. The resulting data structure is, in many cases, more storage efficient than normal linear storage of the data items. This is due to the suppression of duplicate high order bits among the data items. The method allows retrieval of associative data subsets from the associative data set much faster than other multikey access techniques. Analysis of variations on ADAM are suggested, especially for application to very large (over 100000 data items per data set) multiuser databases. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1982
Accession Number
ADA124674

Entities

People

  • James R. Holten Iii

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Biomedical
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Computer Languages
  • Computer Programming
  • Computer Programs
  • Computer Science
  • Computers
  • Content Addressable Memory
  • Data Storage Systems
  • Database Management Systems
  • Databases
  • Debugging
  • Pattern Recognition
  • Software Development
  • Three Dimensional
  • Trees (Data Structures)
  • Two Dimensional
  • Word Processors

Readers

  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Computer Vision.
  • Parallel and Distributed Computing.