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Extracting the Lowest-Frequency Words: Pitfalls and Possibilities

  • Author(s) / Creator(s)
  • In a medical information extraction system, we use common word association techniques to extract side-effect-related terms. Many of these terms have a frequency of less than five. Standard word-association-based applications disregard the lowest-frequency words, and hence disregard useful information. We therefore devised an extraction system for the full word frequency range. This system computes the significance of association by the log-likelihood ratio and Fisher’s exact test. The output of the system shows a recurrent, corpus-independent pattern in both recall and the number of significant words. We will explain these patterns by the statistical behavior of the lowest-frequency words.We used Dutch verb-particle combinations as a second and independent collocation extraction application to illustrate the generality of the observed phenomena. We will conclude that a) word-association-based extraction systems can be enhanced by also considering the lowest-frequency words, b) significance levels should not be fixed but adjusted for the optimal window size, c) hapax legomena, words occurring only once, should be disregarded a priori in the statistical analysis, and d) the distribution of the targets to extract should be considered in combination with the extraction method.

  • Date created
    2000
  • Subjects / Keywords
  • Type of Item
    Article (Published)
  • DOI
    https://doi.org/10.7939/R3QN5ZN98
  • License
    © 2000 Association for Computational Linguistics
  • Language
  • Citation for previous publication
    • Weeber, M., Vos, R., & Baayen, R. H. (2000). Extracting the Lowest-Frequency Words: Pitfalls and Possibilities. Computational Linguistics, 26(3), 301-317.