| FLAGS: A methodology for adaptive anomaly detection and root cause analysis on sensor data streams by fusing expert knowledge with machine learning B Steenwinckel, D De Paepe, SV Hautte, P Heyvaert, M Bentefrit, ... Future Generation Computer Systems 116, 30-48, 2021 | 88 | 2021 |
| Facilitating the analysis of COVID-19 literature through a knowledge graph B Steenwinckel, G Vandewiele, I Rausch, P Heyvaert, R Taelman, ... International Semantic Web Conference, 344-357, 2020 | 44* | 2020 |
| Csv2kg: Transforming tabular data into semantic knowledge B Steenwinckel, G Vandewiele, F De Turck, F Ongenae SemTab, ISWC Challenge, 2019 | 36 | 2019 |
| Deep learning models for predicting RNA degradation via dual crowdsourcing HK Wayment-Steele, W Kladwang, AM Watkins, DS Kim, B Tunguz, ... Nature Machine Intelligence 4 (12), 1174-1184, 2022 | 31* | 2022 |
| INK: knowledge graph embeddings for node classification B Steenwinckel, G Vandewiele, M Weyns, T Agozzino, FD Turck, ... Data Mining and Knowledge Discovery 36 (2), 620-667, 2022 | 28 | 2022 |
| pyRDF2Vec: A Python Implementation and Extension of RDF2Vec B Steenwinckel, G Vandewiele, T Agozzino, F Ongenae European Semantic Web Conference, 471-483, 2023 | 27* | 2023 |
| A generalized matrix profile framework with support for contextual series analysis D De Paepe, SV Hautte, B Steenwinckel, F De Turck, F Ongenae, ... Engineering Applications of Artificial Intelligence 90, 103487, 2020 | 23 | 2020 |
| Walk extraction strategies for node embeddings with rdf2vec in knowledge graphs B Steenwinckel, G Vandewiele, P Bonte, M Weyns, H Paulheim, ... Database and Expert Systems Applications-DEXA 2021 Workshops: BIOKDD, IWCFS …, 2021 | 21* | 2021 |
| Towards adaptive anomaly detection and root cause analysis by automated extraction of knowledge from risk analyses B Steenwinckel, P Heyvaert, D De Paepe, O Janssens, S Vanden Hautte, ... 9th International Semantic Sensor Networks Workshop, Co-Located with 17th …, 2018 | 21 | 2018 |
| Adaptive anomaly detection and root cause analysis by fusing semantics and machine learning B Steenwinckel The Semantic Web: ESWC 2018 Satellite Events: ESWC 2018 Satellite Events …, 2018 | 19 | 2018 |
| A dynamic dashboarding application for fleet monitoring using semantic web of things technologies S Vanden Hautte, P Moens, J Van Herwegen, D De Paepe, ... Sensors 20 (4), 1152, 2020 | 16 | 2020 |
| Data analytics for health and connected care: Ontology, knowledge graph and applications B Steenwinckel, M De Brouwer, M Stojchevska, J Van Der Donckt, J Nelis, ... International Conference on Pervasive Computing Technologies for Healthcare …, 2022 | 15 | 2022 |
| MAGIC: Mining an Augmented Graph using INK, starting from a CSV B Steenwinckel, F De Turck, F Ongenae Proceedings of the Semantic Web Challenge on Tabular Data to Knowledge Graph …, 2021 | 15 | 2021 |
| Assessing the added value of context during stress detection from wearable data M Stojchevska, B Steenwinckel, J Van Der Donckt, M De Brouwer, A Goris, ... BMC Medical Informatics and Decision Making 22 (1), 268, 2022 | 13 | 2022 |
| Inducing a decision tree with discriminative paths to classify entities in a knowledge graph G Vandewiele, B Steenwinckel, F Ongenae, F De Turck SEPDA2019, the 4th International workshop on semantics-powered data mining …, 2019 | 12 | 2019 |
| mBrain: towards the continuous follow-up and headache classification of primary headache disorder patients M De Brouwer, N Vandenbussche, B Steenwinckel, M Stojchevska, ... BMC Medical Informatics and Decision Making 22 (1), 87, 2022 | 9 | 2022 |
| MINDWALC: mining interpretable, discriminative walks for classification of nodes in a knowledge graph G Vandewiele, B Steenwinckel, FD Turck, F Ongenae BMC Medical Informatics and Decision Making 20, 1-15, 2020 | 9 | 2020 |
| A complete software stack for IoT time-series analysis that combines semantics and machine learning—lessons learned from the Dyversify project D De Paepe, S Vanden Hautte, B Steenwinckel, P Moens, J Vaneessen, ... Applied Sciences 11 (24), 11932, 2021 | 7 | 2021 |
| Event-driven dashboarding and feedback for improved event detection in predictive maintenance applications P Moens, S Vanden Hautte, D De Paepe, B Steenwinckel, S Verstichel, ... Applied Sciences 11 (21), 10371, 2021 | 7 | 2021 |
| Conditional constraints for knowledge graph embeddings M Weyns, P Bonte, B Steenwinckel, F De Turck, F Ongenae Workshop on Deep Learning for Knowledge Graphs (DL4KG2020), co-located with …, 2020 | 7 | 2020 |
