Using syntactic distributional patterns for data-driven answer extraction from the Web

Alejandro Figueroa, John Atkinson

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

1 Citation (Scopus)

Abstract

In this work, a data-driven approach for extracting answers from web-snippets is presented. Answers are identified by matching contextual distributional patterns of the expected answer type(EAT) and answer candidates. These distributional patterns are directly learnt from previously annotated tuples {question, sentence, answer}, and the learning mechanism is based on the principles language acquisition. Results shows that this linguistic motivated data-driven approach is encouraging.

Original languageEnglish
Title of host publicationMICAI 2006
Pages985-995
Number of pages11
Volume4293 LNAI
Publication statusPublished - 2006
Event5th Mexican International Conference on Artificial Intelligence, MICAI 2006: Advances in Artificial Intelligence - Apizaco, Mexico
Duration: 13 Nov 200617 Nov 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4293 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other5th Mexican International Conference on Artificial Intelligence, MICAI 2006: Advances in Artificial Intelligence
Country/TerritoryMexico
CityApizaco
Period13/11/0617/11/06

Keywords

  • Natural language processing
  • Question answering

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

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