In this paper we introduce some of the key NLP-related problems related to the practice of Evidence Based Medicine and propose the task of multi-document query-focused summarisation as a key approach to solve these problems. We have completed a corpus for the development of such multi-document query-focused summarisation task. The process to build the corpus combined the use of automated extraction of text, manual annotation, and crowdsourcing to find the reference IDs. We perform a statistical analysis of the corpus for the particular use of single-document summarisation and show that there is still a lot of room for improvement from the current baselines.
%0 Conference Paper
%1 Molla:2011
%A Mollá, Diego
%A Santiago-Martínez, Maria Elena
%B Proceedings ALTA 2011
%D 2011
%K biomedical corpus molla_publication myown
%T Development of a Corpus for Evidence Based Medicine Summarisation
%X In this paper we introduce some of the key NLP-related problems related to the practice of Evidence Based Medicine and propose the task of multi-document query-focused summarisation as a key approach to solve these problems. We have completed a corpus for the development of such multi-document query-focused summarisation task. The process to build the corpus combined the use of automated extraction of text, manual annotation, and crowdsourcing to find the reference IDs. We perform a statistical analysis of the corpus for the particular use of single-document summarisation and show that there is still a lot of room for improvement from the current baselines.
@inproceedings{Molla:2011,
abstract = {In this paper we introduce some of the key NLP-related problems related to the practice of Evidence Based Medicine and propose the task of multi-document query-focused summarisation as a key approach to solve these problems. We have completed a corpus for the development of such multi-document query-focused summarisation task. The process to build the corpus combined the use of automated extraction of text, manual annotation, and crowdsourcing to find the reference IDs. We perform a statistical analysis of the corpus for the particular use of single-document summarisation and show that there is still a lot of room for improvement from the current baselines.},
added-at = {2011-11-16T08:49:50.000+0100},
author = {Moll{\'a}, Diego and Santiago-Mart{\'i}nez, Maria Elena},
biburl = {https://www.bibsonomy.org/bibtex/2b9f0fa9d3e81750dd3731220af28b784/diego_ma},
booktitle = {Proceedings ALTA 2011},
interhash = {792e5066d52bf4464616ec08bc5eacbe},
intrahash = {b9f0fa9d3e81750dd3731220af28b784},
keywords = {biomedical corpus molla_publication myown},
timestamp = {2013-12-12T23:54:40.000+0100},
title = {Development of a Corpus for Evidence Based Medicine Summarisation},
year = 2011
}