Improved POS-tagging for Arabic by combining diverse taggers

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

  • Authors:
  • Maytham Alabbas
  • Allan Ramsay

Abstract

A number of POS-taggers for Arabic have been presented in the literature. These taggers are not in general 100% accurate, and any errors in tagging are likely to lead to errors in the next step of natural language processing. The current work shows an investigation of how the best taggers available today can be improved by combining them. Experimental results show that a very simple approach to combining taggers can lead to significant improvements over the best individual tagger. © 2012 IFIP International Federation for Information Processing.

Bibliographical metadata

Original languageEnglish
Title of host publicationIFIP Advances in Information and Communication Technology|IFIP Advances in Information and Communication Technology
Place of PublicationBerkin
PublisherSpringer Nature
Pages107-116
Number of pages9
Volume381
ISBN (Print)9783642334085
DOIs
Publication statusPublished - 2012
Event8th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2012 - Halkidiki
Event duration: 1 Jul 2012 → …
http://dx.doi.org/10.1007/978-3-642-33409-2_12

Publication series

NameIFIP Advances in Information and Communication Technology,

Conference

Conference8th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2012
CityHalkidiki
Period1/07/12 → …
Internet address