dc.contributor.author | Steenwinckel, Bram | |
dc.contributor.author | Vandewiele, Gilles | |
dc.contributor.author | Weyns, Michael | |
dc.contributor.author | Agozzino, T. | |
dc.contributor.author | De Turck, Filip | |
dc.contributor.author | Ongenae, Femke | |
dc.date.accessioned | 2022-04-29T10:26:25Z | |
dc.date.available | 2022-01-13T10:13:53Z | |
dc.date.available | 2022-04-29T10:26:25Z | |
dc.date.issued | 2022 | |
dc.identifier.issn | 1384-5810 | |
dc.identifier.other | WOS:000738439600009 | |
dc.identifier.uri | https://imec-publications.be/handle/20.500.12860/38742.2 | |
dc.source | WOS | |
dc.title | INK: knowledge graph embeddings for node classification | |
dc.type | Journal article | |
dc.contributor.imecauthor | Steenwinckel, Bram | |
dc.contributor.imecauthor | Vandewiele, Gilles | |
dc.contributor.imecauthor | Weyns, Michael | |
dc.contributor.imecauthor | De Turck, Filip | |
dc.contributor.imecauthor | Ongenae, Femke | |
dc.contributor.orcidimec | Steenwinckel, Bram::0000-0002-3488-2334 | |
dc.contributor.orcidimec | Weyns, Michael::0000-0002-6157-5997 | |
dc.contributor.orcidimec | Ongenae, Femke::0000-0003-2529-5477 | |
dc.contributor.orcidimec | Vandewiele, Gilles::0000-0001-9531-0623 | |
dc.contributor.orcidimec | De Turck, Filip::0000-0003-4824-1199 | |
dc.date.embargo | 9999-12-31 | |
dc.identifier.doi | 10.1007/s10618-021-00806-z | |
dc.source.numberofpages | 48 | |
dc.source.peerreview | yes | |
dc.source.beginpage | 620 | |
dc.source.endpage | 667 | |
dc.source.journal | DATA MINING AND KNOWLEDGE DISCOVERY | |
dc.source.issue | 2 | |
dc.source.volume | 36 | |
imec.availability | Published - open access | |
dc.description.wosFundingText | Bram Steenwinckel (1SA0219N), Gilles Vandewiele (1S31417N) and Michael Weyns (1SD8821N) are funded by a strategic base research Grant of the Fund for Scientific Research Flanders (FWO). This research is part of the imec.ICON project PROTEGO (HBC.2019.2812), co-funded by imec, VLAIO, Televic, Amaron, Z-Plus and ML2Grow. | |