| Crowdtruth: Machine-human computation framework for harnessing disagreement in gathering annotated data O Inel, K Khamkham, T Cristea, A Dumitrache, A Rutjes, J van der Ploeg, ... International semantic web conference, 486-504, 2014 | 82 | 2014 |
| Work and play: An experiment in enterprise gamification LC Stanculescu, A Bozzon, RJ Sips, GJ Houben Proceedings of the 19th ACM Conference on Computer-Supported Cooperative …, 2016 | 78 | 2016 |
| “Dr. Detective”: combining gamification techniques and crowdsourcing to create a gold standard in medical text A Dumitrache, L Aroyo, C Welty, RJ Sips, A Levas Proceedings of the 1st International Workshop on Crowdsourcing the Semantic …, 2013 | 40 | 2013 |
| Domain-independent quality measures for crowd truth disagreement O Inel13, L Aroyo, C Welty, RJ Sips Detection, Representation, and Exploitation of Events in the Semantic Web, 2, 2013 | 22* | 2013 |
| Evaluating neural text simplification in the medical domain L Van den Bercken, RJ Sips, C Lofi The World Wide Web Conference, 3286-3292, 2019 | 19 | 2019 |
| Utilizing data mining for predictive modeling of colorectal cancer using electronic medical records M Hoogendoorn, LMG Moons, ME Numans, RJ Sips International Conference on Brain Informatics and Health, 132-141, 2014 | 15 | 2014 |
| Empirically-derived Methodology for Crowdsourcing Ground Truth A Dumitrache, O Inel, B Timmermans, C Ortiz, RJ Sips, L Aroyo | 14* | 2020 |
| Online social network evolution: Revisiting the Twitter graph H Efstathiades, D Antoniades, G Pallis, MD Dikaiakos, Z Szlávik, RJ Sips 2016 IEEE International Conference on Big Data (Big Data), 626-635, 2016 | 11 | 2016 |
| Decision support framework for opening business data A Buda, J Ubacht, M Janssen, RJ Sips ECEG2016-Proceedings of 16th European Conference on e-Government ECEG 2016, 29, 2016 | 8 | 2016 |
| Applying intention-based guidelines for critiquing R Sips, L Braun, N Roos ECAI, 83-8, 2006 | 8* | 2006 |
| Nudge your workforce. a study on the effects of task notification strategies in enterprise mobile crowdsourcing S Bashirieh, S Mesbah, J Redi, S SzlĂąvik, RJ Sips International Conference on User Modelling, Adaption and Personalisation (UMAP), 2017 | 7* | 2017 |
| A study of the online profile of enterprise users in professional social networks A Bozzon, H Efstathiades, GJ Houben, RJ Sips Proceedings of the 23rd International Conference on World Wide Web, 487-492, 2014 | 6 | 2014 |
| The inclusive enterprise: Vision and roadmap RJ Sips, A Bozzon, G Smit, GJ Houben International Conference on Web Engineering, 621-624, 2015 | 5 | 2015 |
| Crowd watson: Crowdsourced text annotations H Lin, O Inel, G Soberón, L Aroyo, C Welty, M Overmeen, RJ Sips Technical report, VU University Amsterdam, 2013 | 5 | 2013 |
| Training data augmentation for detecting adverse drug reactions in user-generated content S Mesbah, J Yang, RJ Sips, MV Torre, C Lofi, A Bozzon, GJ Houben Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 4 | 2019 |
| Crowdsourcing ground truth data for analysing brainstem tumors in children B Timmermans, Z Szlavik, RJ Sips Proceedings of the 28th Benelux Conference on Artificial Intelligence …, 2016 | 3 | 2016 |
| Give it a shot: Few-shot learning to normalize ADR mentions in Social Media posts E Manousogiannis, S Mesbah, A Bozzon, S Baez, RJ Sips Proceedings of the Fourth Social Media Mining for Health Applications …, 2019 | 2 | 2019 |
| ENABLING MEDICAL EXPERT CRITIQUING USING A BDI APPROACH RJ Sipsa, L Brauna, N Roosa Proc. BeNeLux conf. artif. intell. 2006, 2006 | 2* | 2006 |
| Enabling protocol-based medical critiquing A Hasman Ubiquity: technologies for better health in aging societies: proceedings of …, 2006 | 2* | 2006 |
| Crowdsourcing for Video Event Detection R IEPSMA, T GEVERS, O INEL, L AROYO, RJAN SIPS, Z SZLAVIK Collective Intelligence, 2017 | 1 | 2017 |
Lora AroyoResearch Scientists @Google Research NYCVerified email at google.com
