Experiments with a Sparse Distributed Memory for Text Classification

  • Mateus Mendes
  • A. Paulo Coimbra
  • Manuel M. Crisóstomo
  • Jorge Rodrigues
Conference paper

Abstract

The Sparse Distributed Memory (SDM) has been studied for decades as a theoretical model of an associative memory in many aspects similar to the human brain. It has been tested for different purposes. The present work describes its use as a quick text classifier, based on pattern similarity only. The results found with different datasets were superior to the performance of the dumb classifier or purely random choice, even without text preprocessing. Experiments were performed with a popular Reuters newsgroups dataset and also for real time web ad serving.

Keywords

SDM Sparse distributed memory Text classification Text comparison Long range correlations Vector space model 

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Mateus Mendes
    • 1
    • 2
  • A. Paulo Coimbra
    • 2
  • Manuel M. Crisóstomo
    • 2
  • Jorge Rodrigues
    • 1
    • 2
  1. 1.ESTGOHPolytechnic Institute of CoimbraCoimbraPortugal
  2. 2.Institute of Systems and Robotics, Pólo IIUniversity of CoimbraCoimbraPortugal

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