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
Subtitle of host publicationAdvances in Artificial Intelligence - 5th Mexican International Conference on Artificial Intelligence, Proceedings
PublisherSpringer Verlag
Pages985-995
Number of pages11
ISBN (Print)3540490264, 9783540490265
DOIs
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)0302-9743
ISSN (Electronic)1611-3349

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

  • Theoretical Computer Science
  • General Computer Science

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