Domain-General Versus Domain-Specific Named Entity Recognition: A Case Study Using TEXT

Cheng Yang Lim, Ian K. T. Tan*, Bhawani Selvaretnam

*Corresponding author for this work

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

2 Citations (Scopus)

Abstract

Named entity recognition (NER) seeks to identify and classify named entities within bodies of text into language categories such as nouns, that are reflective of locations, organizations, and people. As it is language dependent, the approach taken for most NER systems are domain-general, meaning that they are designed based on a language and not on a specific targeted domain. With current usage of non-formal languages on social media, this instigates the need to compare the performance of domain-general and domain specific NERs. A domain specific NER (vehicle traffic domain), TEXT, is described and the performance of domain-general NER versus TEXT is compared. The results of the evaluation show that the performance of domain-specific NER significantly outperforms domain-general NER. The domain-general NER could only perform adequately for common scenarios.

Original languageEnglish
Title of host publicationMulti-disciplinary Trends in Artificial Intelligence. MIWAI 2019
EditorsRapeeporn Chamchong, Kok Wai Wong
PublisherSpringer
Pages238-246
Number of pages9
ISBN (Electronic)9783030337094
ISBN (Print)9783030337087
DOIs
Publication statusPublished - 21 Oct 2019
Event13th Multi-disciplinary International Conference on Artificial Intelligence 2019 - Kuala Lumpur, Malaysia
Duration: 17 Nov 201919 Nov 2019

Publication series

NameLecture Notes in Computer Science
Volume11909
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th Multi-disciplinary International Conference on Artificial Intelligence 2019
Abbreviated titleMIWAI 2019
Country/TerritoryMalaysia
CityKuala Lumpur
Period17/11/1919/11/19

Keywords

  • Domain-general
  • Domain-specific
  • Information extraction
  • Named Entity Recognition
  • Traffic

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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