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A VNS-based quartet algorithm for biomedical literature clustering

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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.
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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