{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T16:11:45Z","timestamp":1781107905800,"version":"3.54.1"},"reference-count":33,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,11,9]],"date-time":"2022-11-09T00:00:00Z","timestamp":1667952000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,11,9]],"date-time":"2022-11-09T00:00:00Z","timestamp":1667952000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,11,9]]},"DOI":"10.23919\/fruct56874.2022.9953859","type":"proceedings-article","created":{"date-parts":[[2022,11,28]],"date-time":"2022-11-28T20:25:13Z","timestamp":1669667113000},"page":"196-203","source":"Crossref","is-referenced-by-count":2,"title":["Enterprise Modelling Assistance: Edge Prediction Improvement Using Textual Information"],"prefix":"10.23919","author":[{"given":"Walaa","family":"Othman","sequence":"first","affiliation":[{"name":"ITMO University,St.Petersburg,Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nikolay","family":"Shilov","sequence":"additional","affiliation":[{"name":"SPC RAS, St.Petersburg, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref33","article-title":"Modeling method conceptualization within omilab: The 4em case","author":"stirna","year":"2017","journal-title":"PoEM"},{"key":"ref32","first-page":"2116","article-title":"Unsupervised cross-lingual representation learning at scale","volume":"abs 1911","author":"conneau","year":"2019","journal-title":"CoRR"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.747"},{"key":"ref30","first-page":"10957","article-title":"Minilm: Deep self-attention distillation for task-agnostic compression of pre-trained transformers","volume":"abs 2002","author":"wang","year":"2020","journal-title":"CoRR"},{"key":"ref10","article-title":"Entity context and relational paths for knowledge graph completion","volume":"abs 2002 6757","author":"wang","year":"2020","journal-title":"CoRR"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623732"},{"key":"ref12","article-title":"Translating embeddings for modeling multi-relational data","volume":"26","author":"bordes","year":"2013","journal-title":"Advances in neural information processing systems"},{"key":"ref13","first-page":"10197","article-title":"Rotate: Knowledge graph embedding by relational rotation in complex space","volume":"abs 1902","author":"sun","year":"2019","journal-title":"CoRR"},{"key":"ref14","first-page":"4910","article-title":"Orthogonal relation transforms with graph context modeling for knowledge graph embedding","volume":"abs 1911","author":"tang","year":"2019","journal-title":"CoRR"},{"key":"ref15","first-page":"9419","article-title":"Learning hierarchy-aware knowledge graph embeddings for link prediction","volume":"abs 1911","author":"zhang","year":"2019","journal-title":"CoRR"},{"key":"ref16","volume":"12","author":"bruna","year":"2013","journal-title":"Spectral networks and locally connected networks on graphs"},{"key":"ref17","article-title":"Inductive representation learning on large graphs","author":"hamilton","year":"2017","journal-title":"CoRR vol abs\/1706 02216"},{"key":"ref18","first-page":"7829","article-title":"Dynamic graph CNN for learning on point clouds","volume":"abs 1801","author":"wang","year":"2018","journal-title":"CoRR"},{"key":"ref19","first-page":"9691","article-title":"Link prediction based on graph neural networks","volume":"abs 1802","author":"zhang","year":"2018","journal-title":"CoRR"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D17-1070"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.ifacol.2022.04.191"},{"key":"ref27","first-page":"0","article-title":"Siamese neural networks for one-shot image recognition","volume":"2","author":"koch","year":"2015","journal-title":"ICML Deep Learning Workshop"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2021.107485"},{"key":"ref6","first-page":"19","article-title":"Machine learning-based enterprise modeling assistance: Approach and poten-tials","volume":"432","author":"shilov","year":"0","journal-title":"The Practice of Enterprise Modeling 14th IFIP WG 8 1 Working Conference PoEM 2021 Riga Latvia November 24–26 2021 Proceedings ser Lecture Notes in Business Information Processing"},{"key":"ref29","first-page":"11175","article-title":"Universal sentence encoder","volume":"abs 1803","author":"cer","year":"2018","journal-title":"CoRR"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/s12599-018-0517-5"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1002\/asi.20591"},{"key":"ref7","first-page":"1999","article-title":"The pagerank citation ranking: Bringing order to the web","author":"page","year":"1999","journal-title":"Stanford InfoLab Technical Report"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2021.148539"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/P15-1016"},{"key":"ref1","first-page":"181","author":"zimmermann","year":"2021","journal-title":"Architecting Digital Products and Services"},{"key":"ref20","first-page":"142","article-title":"Distance encoding - design provably more powerful graph neural networks for structural representation learning","author":"li","year":"2009","journal-title":"CoRR"},{"key":"ref22","first-page":"4546","article-title":"Distributed representations of words and phrases and their compositionality","volume":"abs 1310","author":"mikolov","year":"2013","journal-title":"CoRR"},{"key":"ref21","first-page":"1532","volume":"14","author":"pennington","year":"2014","journal-title":"GloVe Global Vectors for Word Representation"},{"key":"ref24","first-page":"4805","article-title":"BERT: pre-training of deep bidirectional transformers for language understanding","volume":"abs 1810","author":"devlin","year":"2018","journal-title":"CoRR"},{"key":"ref23","first-page":"4606","article-title":"Enriching word vectors with subword information","volume":"abs 1607","author":"bojanowski","year":"2016","journal-title":"CoRR"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1410"},{"key":"ref25","article-title":"Distributed representations of sentences and documents","volume":"4","author":"le","year":"0","journal-title":"31st International Conference on Machine Learning"}],"event":{"name":"2022 32nd Conference of Open Innovations Association (FRUCT)","location":"Tampere, Finland","start":{"date-parts":[[2022,11,9]]},"end":{"date-parts":[[2022,11,11]]}},"container-title":["2022 32nd Conference of Open Innovations Association (FRUCT)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9953737\/9953804\/09953859.pdf?arnumber=9953859","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,14]],"date-time":"2023-02-14T19:11:53Z","timestamp":1676401913000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9953859\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,9]]},"references-count":33,"URL":"https:\/\/doi.org\/10.23919\/fruct56874.2022.9953859","relation":{},"subject":[],"published":{"date-parts":[[2022,11,9]]}}}