This paper proposes a methodology that is able to search for relevant references for
systematic reviews and meta-analysis from theMedline/PubMed database, and then
to visualize the retrieved bibliography through the quartet method of hierarchical
clustering. As this novel approach is based on a NP-hard combinatorial problem, a
Reduced Variable Neighbourhood Search is used to produce the graph of document
clusters as output from the input distance matrix whereby the number of clusters
is not known in advance. The distance matrix is derived from the link-ranking
XML data returned by PubMed with the search results. The method allows to
retrieve intuitively biomedical-related bibliography, and to detect the structure of
the literature collection examined.
Keywords: Hierarchical clustering, quartets, variable neighbourhood search,
biomedical information extraction, data representation, graphs.
CONSOLI Sergio;
STILIANAKIS Nikolaos;
2015-02-24
ELSEVIER BV
JRC91081
1571-0653,
http://www.sciencedirect.com/science/article/pii/S1571065314000456,
https://publications.jrc.ec.europa.eu/repository/handle/JRC91081,
10.1016/j.endm.2014.11.003,
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