Towards two-step multi-document summarisation for evidence based medicine: a quantitative analysis

Abeed Sarker, Diego Mollá-Aliod, Cécile Paris

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Abstract

We perform a quantitative analysis of data in a corpus that specialises on summarisation for Evidence Based Medicine (EBM). The intent of the analysis is to discover possible directions for performing automatic evidence-based summarisation. Our analysis attempts to ascertain the extent to which good, evidence-based, multidocument summaries can be obtained from individual single-document summaries of the source texts. We define a set of scores, which we call coverage scores, to estimate the degree of information overlap between the multi-document summaries and source texts of various granularities. Based on our analysis, using several variants of the coverage scores, and the results of a simple task oriented evaluation, we argue that approaches for the automatic generation of evidence-based, bottom-line, multi-document summaries may benefit by utilising a two-step approach: in the first step, content-rich, singledocument, query-focused summaries are generated; followed by a step to synthesise the information from the individual summaries.
Original languageEnglish
Pages (from-to)79-87
Number of pages9
JournalProceedings of the Australasian Language Technology Association Workshop 2012 : ALTA 2012
Volume10
Publication statusPublished - 2012
EventAustralasian Language Technology Workshop (10th : 2012) - Dunedin, New Zealand
Duration: 4 Dec 20126 Dec 2012

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