An approach for query-focused text summarisation for evidence based medicine

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

6 Citations (Scopus)

Abstract

We present an approach for extractive, query-focused, single-document summarisation of medical text. Our approach utilises a combination of target-sentence-specific and target-sentence-independent statistics derived from a corpus specialised for summarisation in the medical domain. We incorporate domain knowledge via the application of multiple domain-specific features, and we customise the answer extraction process for different question types. The use of carefully selected domain-specific features enables our summariser to generate content-rich extractive summaries, and an automatic evaluation of our system reveals that it outperforms other baseline and benchmark summarisation systems with a percentile rank of 96.8%.

Original languageEnglish
Title of host publicationArtificial Intelligence in Medicine
Subtitle of host publication14th Conference on Artificial Intelligence in Medicine, AIME 2013, Murcia, Spain, May 29 – June 1, 2013. Proceedings
EditorsNiels Peek, Roque Marín Morales, Mor Peleg
Place of PublicationHeidelberg
PublisherSpringer, Springer Nature
Pages295-304
Number of pages10
ISBN (Electronic)9783642383267
ISBN (Print)9783642383250
DOIs
Publication statusPublished - 2013
Event14th Conference on Artificial Intelligence in Medicine, AIME 2013 - Murcia, Spain
Duration: 29 May 20131 Jun 2013

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Berlin Heidelberg
Volume7885
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other14th Conference on Artificial Intelligence in Medicine, AIME 2013
CountrySpain
CityMurcia
Period29/05/131/06/13

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