From post

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed.

 

Другие публикации лиц с тем же именем

CrowdTruth 2.0: Quality Metrics for Crowdsourcing with Disagreement., , , , и . CoRR, (2018)Achieving Expert-Level Annotation Quality with CrowdTruth: The Case of Medical Relation Extraction., , и . BDM2I@ISWC, том 1428 из CEUR Workshop Proceedings, CEUR-WS.org, (2015)"Dr. Detective": combining gamification techniques and crowdsourcing to create a gold standard in medical text., , , , и . CrowdSem, том 1030 из CEUR Workshop Proceedings, стр. 16-31. CEUR-WS.org, (2013)False Positive and Cross-relation Signals in Distant Supervision Data., , и . AKBC@NIPS, OpenReview.net, (2017)Crowdsourcing Ground Truth for Medical Relation Extraction., , и . ACM Trans. Interact. Intell. Syst., 8 (2): 11:1-11:20 (2018)SemEval-2021 Task 12: Learning with Disagreements., , , , , , , и . SemEval@ACL/IJCNLP, стр. 338-347. Association for Computational Linguistics, (2021)Crowdsourcing Inclusivity: Dealing with Diversity of Opinions, Perspectives and Ambiguity in Annotated Data., , , , , и . WWW (Companion Volume), стр. 1294-1295. ACM, (2019)Crowdsourcing Ground Truth for Medical Relation Extraction., , и . CoRR, (2017)Crowdsourcing Semantic Label Propagation in Relation Classification., , и . CoRR, (2018)CrowdTruth: Machine-Human Computation Framework for Harnessing Disagreement in Gathering Annotated Data., , , , , , , , и . ISWC (2), том 8797 из Lecture Notes in Computer Science, стр. 486-504. Springer, (2014)