20.500.12556/DiRROS-19534 Bisociative literature-based discovery lessons learned and new word embedding approach 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. true false true Angleški jezik Ni določen Neznano 2024-07-19 03:44:01 2024-07-22 11:38:21 2024-07-23 03:55:53 0000-00-00 00:00:00 2020 0 0 str. 773-800 Vol. 38 2020 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 2020-10-06 004.8 0288-3635 10.1007/s00354-020-00108-w 31844867 http://dx.doi.org/10.1007/s00354-020-00108-w 1 9b2f0b69-455f-11ef-b487-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=26935 RAZ_Lavrac_Nada_2020.pdf RAZ_Lavrac_Nada_2020.pdf 1 D27E500857A776CE4BEB355228C19770 b287d8a31aaabb1e91837340a91c223a4f56268fd76707d55085cf41b6783654 772755ed-47fd-11ef-b487-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=27080 Nacionalni inštitut za biologijo 0 0 0