Expanding domain-specific lexicons by term categorization

Henri Avancini, Alberto Lavelli, Bernardo Magnini, Fabrizio Sebastiani, Roberto Zanoli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

22 Citations (Scopus)

Abstract

We discuss an approach to the automatic expansion of domain-specific lexicons by means of term categorization, a novel task employing techniques from information retrieval (IR) and machine learning (ML). Specifically, we view the expansion of such lexicons as a process of learning previously unknown associations between terms and domains. The process generates, for each ci in a set C = {c1,...,cm} of domains, a lexicon L1i, bootstrapping from an initial lexicon L0i and a set of documents θ given as input. The method is inspired by text categorization (TC), the discipline concerned with labelling natural language texts with labels from a predefined set of domains, or categories. However, while TC deals with documents represented as vectors in a space of terms, we formulate the task of term categorization as one in which terms are (dually) represented as vectors in a space of documents, and in which terms (instead of documents) are labelled with domains.

Original languageEnglish
Title of host publicationProceedings of the ACM Symposium on Applied Computing
EditorsG. Lamont
Pages793-797
Number of pages5
Publication statusPublished - 2003
Externally publishedYes
EventProceedings of the 2003 ACM Symposium on Applied Computing - Melbourne, FL
Duration: 9 Mar 200312 Mar 2003

Other

OtherProceedings of the 2003 ACM Symposium on Applied Computing
CityMelbourne, FL
Period9/3/0312/3/03

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Keywords

  • Lexicon generation
  • Term categorization
  • WordNet

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Avancini, H., Lavelli, A., Magnini, B., Sebastiani, F., & Zanoli, R. (2003). Expanding domain-specific lexicons by term categorization. In G. Lamont (Ed.), Proceedings of the ACM Symposium on Applied Computing (pp. 793-797)