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Constructing Empirical Formulas for Testing Word Similarity by the Inductive Method of Model Self-Organization

  • Pavel Makagonov
  • Mikhail Alexandrov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2389)

Abstract

Identification of words with the same base meaning is a necessary procedure for many algorithms of computational linguistics and text processing. We propose to use for this a knowledge-poor approach using an empirical formula based on the number of the coincident letters in the initial parts of the two words and the number of non-coincident letters in the final parts of these two words. To construct such a formula for a given language, we use inductive method of self-organization developed by A. Ivahnenko. This method considers a set of models (formulas) of a given class and selects the best ones using training samples and test samples. We give a detailed example for English. We also show how to apply the formula for creating word frequency list.

Keywords

Empirical Formula Word Pair Automatic Documentation Mathematical Linguistics External Criterion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Pavel Makagonov
    • 1
  • Mikhail Alexandrov
    • 2
  1. 1.Moscow Mayor’s DirectorateMoscow City GovernmentMoscowRussia
  2. 2.Center for Computing ResearchNational Polytechnic Institute (IPN)Mexico

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