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<metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/"><dc:title>Bisociative literature-based discovery</dc:title><dc:creator>Lavrač,	Nada	(Avtor)
	</dc:creator><dc:creator>Martinc,	Matej	(Avtor)
	</dc:creator><dc:creator>Pollak,	Senja	(Avtor)
	</dc:creator><dc:creator>Pompe Novak,	Maruša	(Avtor)
	</dc:creator><dc:creator>Cestnik,	Bojan	(Avtor)
	</dc:creator><dc:description>The field of bisociative literature-based discovery aims at mining scientific literature to reveal yet uncovered connections between different fields of specialization. This paper outlines several outlier-based literature mining approaches to bridging term detection and the lessons learned from selected biomedical literature-based discovery applications. The paper addresses also new prospects in bisociative literature-based discovery, proposing an advanced embeddings-based technology for cross-domain literature mining.</dc:description><dc:date>2020</dc:date><dc:date>2024-07-19 03:44:01</dc:date><dc:type>Neznano</dc:type><dc:identifier>19534</dc:identifier><dc:identifier>UDK: 004.8</dc:identifier><dc:identifier>ISSN pri članku: 0288-3635</dc:identifier><dc:identifier>DOI: 10.1007/s00354-020-00108-w</dc:identifier><dc:identifier>COBISS_ID: 31844867</dc:identifier><dc:language>sl</dc:language></metadata>
