Reviewing and evaluating automatic term recognition techniques

Ioannis Korkontzelos, Ioannis P. Klapaftis, Suresh Manandhar

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

    Abstract

    Automatic Term Recognition (ATR) is defined as the task of identifying domain specific terms from technical corpora. Termhood-based approaches measure the degree that a candidate term refers to a domain specific concept. Unithood-based approaches measure the attachment strength of a candidate term constituents. These methods have been evaluated using different, often incompatible evaluation schemes and datasets. This paper provides an overview and a thorough evaluation of state-of-the-art ATR methods, under a common evaluation framework, i.e. corpora and evaluation method. Our contributions are two-fold: (1) We compare a number of different ATR methods, showing that termhood-based methods achieve in general superior performance. (2) We show that the number of independent occurrences of a candidate term is the most effective source for estimating term nestedness, improving ATR performance. © 2008 Springer-Verlag Berlin Heidelberg.
    Original languageEnglish
    Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.
    PublisherSpringer Nature
    Pages248-259
    Number of pages11
    Volume5221
    ISBN (Print)3540852867, 9783540852865
    DOIs
    Publication statusPublished - 2008
    Event6th International Conference on Natural Language Processing, GoTAL 2008 - Gothenburg
    Duration: 1 Jul 2008 → …
    http://dx.doi.org/10.1007/978-3-540-85287-2\_24

    Publication series

    NameGoTAL '08

    Conference

    Conference6th International Conference on Natural Language Processing, GoTAL 2008
    CityGothenburg
    Period1/07/08 → …
    Internet address

    Keywords

    • ATR
    • Automatic term recognition
    • Term extraction

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