Modeling Temporal Crowd Work Quality with Limited Supervision (original) (raw)

Predicting Next Label Quality: A Time-Series Model of Crowdwork

HyunJoon Jung

The 2nd AAAI Conference on Human Computation & Crowdsourcing (HCOMP) 2014

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An Active Learning Approach for Jointly Estimating Worker Performance and Annotation Reliability with Crowdsourced Data

Gita Sukthankar

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Efficient Worker Selection Through History-Based Learning in Crowdsourcing

Nadia Bennani

2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC), 2017

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A Time-Series-Based New Behavior Trace Model for Crowd Workers That Ensures Quality Annotation

Mohammed FAISAL

Sensors, 2021

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Additional Operations of Simple HITs on Microtask Crowdsourcing for Worker Quality Prediction

Yu Suzuki

Journal of Information Processing, 2019

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Your Behavior Signals Your Reliability: Modeling Crowd Behavioral Traces to Ensure Quality Relevance Annotations

Mucahid Kutlu

The Sixth AAAI Conference on Human Computation and Crowdsourcing, 2018

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Exploiting Worker Correlation for Label Aggregation in Crowdsourcing

Benjamin Rubinstein

2019

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Machine Learning with Crowdsourcing: A Brief Summary of the Past Research and Future Directions

Edwin Meza

Proceedings of the AAAI Conference on Artificial Intelligence, 2019

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A Robust Consistency Model of Crowd Workers in Text Labeling Tasks

Majed AlRubaian

IEEE Access, 2020

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Learning From Noisy Singly-labeled Data

Zachary Lipton

ArXiv, 2018

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An online approach for joint task assignment and worker evaluation in crowd-sourcing

Lorenzo Bracciale

Pervasive and Mobile Computing, 2018

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End-to-End Learning from Noisy Crowd to Supervised Machine Learning Models

CHI HONG AO

2020 IEEE Second International Conference on Cognitive Machine Intelligence (CogMI), 2020

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An Entropic Score to Rank Annotators for Crowdsourced Labeling Tasks

Shipeng Yu

2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics, 2011

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Iterative Bayesian Learning for Crowdsourced Regression

Sewoong Oh

2019

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Time-Sensitive Bayesian Information Aggregation for Crowdsourcing Systems

John Guiver

Journal of Artificial Intelligence Research, 2016

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Octopus: A Framework for Cost-Quality-Time Optimization in Crowdsourcing

Shreya Rajpal

2017

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Toward a Learning Science for Complex Crowdsourcing Tasks

E. Kamar, Shayan Doroudi

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Ability Grouping of Crowd Workers via Reward Discrimination

Tenda Okimoto

2013

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Crowdworker filtering with support vector machine

Hohyon Ryu, Matt Lease

Proc. Am. Soc. Info. Sci. Tech., 2011

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Towards Globally Optimal Crowdsourcing Quality Management

Akash Das Sarma

Proceedings of the 2016 International Conference on Management of Data - SIGMOD '16, 2016

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Cross-task crowdsourcing

Erheng Zhong

Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, 2013

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An impact-driven model for quality control in skewed-domain crowdsourcing tasks

Wolf-tilo Balke

Proceedings of the 8th ACM Conference on Web Science, 2016

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Globally Optimal Crowdsourcing Quality Management: Full technical report

Akash Das Sarma

ArXiv, 2015

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Predicting result quality in Crowdsourcing using application layer monitoring

M. Hirth

2014 IEEE Fifth International Conference on Communications and Electronics (ICCE), 2014

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Efficient Learning for Crowdsourced Regression

Sewoong Oh

ArXiv, 2017

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Fine-Tuning Gold Questions in Crowdsourcing Tasks using Probabilistic and Siamese Neural Network Models

Wolf-tilo Balke

2019

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Crowd-Powered Experts

Carsten Eickhoff

GamifIR 2014 - ECIR Workshop on Gamification for Information Retrieval, 2014

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Crowd Labeling: a survey

Jafar Muhammadi

2014

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Globally Optimal Crowdsourcing Quality Management

Akash Das Sarma

2015

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A Novel Crowd-sourcing Inference Method

William Tang

2019

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Task Recommendation in Crowdsourcing Based on Learning Preferences and Reliabilities

Qiyu Kang

IEEE Transactions on Services Computing

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A Correlated Worker Model for Grouped, Imbalanced and Multitask Data

An Nguyễn

2016

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Batch Reinforcement Learning from Crowds

Kusnindar Priohutomo

ArXiv, 2021

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