Pseudo relevance feedback using named entities for question answering

Luiz Augusto Pizzato, Diego Mollá, Cécile Paris

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

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Abstract

Relevance feedback has already proven its usefulness in probabilistic information retrieval (IR). In this research we explore whether a pseudo relevance feedback technique on IR can improve the Question Answering task (QA). The basis of our exploration is the use of relevant named entities from the top retrieved documents as clues of relevance. We discuss two interesting findings from these experiments: the reasons the results were not improved, and the fact that today’s metrics of IR evaluation on QA do not reflect the results obtained by a QA system.
Original languageEnglish
Title of host publicationProceedings of the 2006 Australasian language technology workshop 2006, November 30-December 1, 2006, Sancta Sophia College, Sydney
EditorsLawrence Cavedon, Ingrid Zukerman
Place of PublicationSydney
PublisherAustralasian Language Technology Association
Pages83-90
Number of pages8
ISBN (Print)1741081467
Publication statusPublished - 2006
EventAustralasian Language Technology Association Workshop - Sydney
Duration: 30 Nov 20061 Dec 2006

Publication series

NameProceedings of the Australasian Language Technology Workshop
PublisherAustralasian Language Technology Association
ISSN (Print)1834-7037

Workshop

WorkshopAustralasian Language Technology Association Workshop
CitySydney
Period30/11/061/12/06

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