Supervised learning algorithms applied to terminology extraction

ROGELIO ANTONIO NAZAR, Maria Teresa Cabré

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

In this paper we present a new terminology extraction system based on supervised statistical learning algorithms, which are characterized by having a training phase with a controlled exposure to both positive and negative examples prior to the actual categorization. Contrary to the vast majority of the term extractors reported in the literature, our proposal is based on implicit knowledge rather than handcrafted explicit rules. Given a list of terms from some domain and language plus a general language reference corpus, we developed a methodology for terminology extraction and implemented it as a web application that is already available online. This tool is flexible enough to operate in different languages and domains and, as a sort of lifelong learning algorithm, it turns terminology extraction into a collaborative effort, where all users benefit from the training conducted by each individual.

Original languageEnglish
Title of host publicationProceedings of the 10th Terminology and Knowledge Engineering Conference
Subtitle of host publicationNew Frontiers in the Constructive Symbiosis of Terminology and Knowledge Engineering, TKE 2012
Pages209-217
Number of pages9
StatePublished - 2012
Externally publishedYes
Event10th Terminology and Knowledge Engineering Conference: New Frontiers in the Constructive Symbiosis of Terminology and Knowledge Engineering, TKE 2012 - Madrid, Spain
Duration: 19 Jun 201222 Jun 2012

Publication series

NameProceedings of the 10th Terminology and Knowledge Engineering Conference: New Frontiers in the Constructive Symbiosis of Terminology and Knowledge Engineering, TKE 2012

Conference

Conference10th Terminology and Knowledge Engineering Conference: New Frontiers in the Constructive Symbiosis of Terminology and Knowledge Engineering, TKE 2012
CountrySpain
CityMadrid
Period19/06/1222/06/12

Keywords

  • Computational terminography
  • Machine learning
  • Quantitative linguistics
  • Terminology extraction

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