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Robert-Jan Sips
Robert-Jan Sips
TKH Group
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Title
Cited by
Cited by
Year
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
1262016
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, ...
The Semantic Web–ISWC 2014: 13th International Semantic Web Conference, Riva …, 2014
1112014
Evaluating neural text simplification in the medical domain
L Van den Bercken, RJ Sips, C Lofi
The World Wide Web Conference, 3286-3292, 2019
822019
Dr. Detective: combining gamification techniques and crowdsourcing to create a gold standard for the medical domain
A Dumitrache, L Aroyo, C Welty, RJ Sips, A Levas
Crowdsourcing the Semantic Web, 2013
512013
Empirically-derived Methodology for Crowdsourcing Ground Truth
A Dumitrache, O Inel, B Timmermans, C Ortiz, RJ Sips, L Aroyo
29*2020
Decision support framework for opening business data
A Buda, J Ubacht, M Janssen, RJ Sips
ECEG2016-Proceedings of 16th European Conference on e-Government, 29, 2016
182016
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
172016
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
152014
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
142019
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
142013
Nudge your workforce. a study on the effects of task notification strategies in enterprise mobile crowdsourcing
S Bashirieh, S Mesbah, Z Szlávik, RJ Sips, J Redi, A Bozzon, PG Lopez, ...
Proceedings of 25th International Conference on User Modelling, Adaption and …, 2017
11*2017
Applying intention-based guidelines for critiquing
R Sips, L Braun, N Roos
ECAI, 83-8, 2006
10*2006
Exploiting Crowdsourcing Disagreement with Various Domain-Independent Quality Measures
OA Inel, LM Aroyo, C Welty, RJ Sips
DeRiVE 2013 Workshop, ISWC, 2013
82013
Give it a shot: Few-shot learning to normalize ADR mentions in Social Media posts
E Manousogiannis, S Mesbah, A Bozzon, SB Santamaría, RJ Sips
Proceedings of the Fourth Social Media Mining for Health Applications …, 2019
72019
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
62014
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
52016
What do You Mean, Doctor? A Knowledge-based Approach for Word Sense Disambiguation of Medical Terminology.
EV Godinez, Z Szlávik, E Contempré, RJ Sips
HEALTHINF, 273-280, 2021
42021
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
42013
Evaluating medical lexical simplification: rule-based vs. BERT
L Tran, E Velazquez, RJ Sips, V de Boer
Public Health and Informatics, 1023-1024, 2021
32021
Language Identification for Short Medical Texts.
EV Godinez, Z Szlávik, SB Santamaría, RJ Sips
HEALTHINF, 399-406, 2020
32020
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Articles 1–20