Clustering and classification of reference documents from large-scale literature searches: Support to the SAM explanatory note "New Techniques in Agricultural Biotechnology"
Searches of the existing scientific literature are the cornerstone of scientific research and reporting. With the constant growth of the rate at which scientific studies and reviews are being published, the information produced by these searches can be delicate to manage. Narrowing the search increases the risk of overlooking important documents, while broadening it can produce too many documents to be reasonably processed.
This report describes a set of strategies designed to process large sets of scientific references (such as those obtained by broad literature searches) and assist in the identification of documents relevant for specific purposes. These strategies take advantage of metadata associated to each document in SCOPUS, the database of peer-reviewed literature maintained by Elsevier and accessible through an Application Programming Interface (API).
These strategies were developed and applied in support to the European Commission's Scientific Advice Mechanism (SAM) in managing the results of literature searches in the context of the exploratory note "New Techniques in Agricultural Biotechnology".
ANGERS Alexandre;
PETRILLO Mauro;
2017-05-29
Publications Office of the European Union
JRC106191
978-92-79-69019-8,
1831-9424,
EUR 28618 EN,
OP KJ-NA-28618-EN-N,
https://publications.jrc.ec.europa.eu/repository/handle/JRC106191,
10.2760/256470,
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