A worker clustering-based approach of label aggregation under the belief function theory (original) (raw)

Exploiting Worker Correlation for Label Aggregation in Crowdsourcing

Benjamin Rubinstein

2019

View PDFchevron_right

Debiased Label Aggregation for Subjective Crowdsourcing Tasks

Shaun Wallace

CHI Conference on Human Factors in Computing Systems Extended Abstracts

View PDFchevron_right

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

View PDFchevron_right

A Novel Label Aggregation with Attenuated Scores for Ground-Truth Identification of Dataset Annotation with Crowdsourcing

Charnyote Pluempitiwiriyawej

IEICE Transactions on Information and Systems, 2017

View PDFchevron_right

An Evaluation of Aggregation Techniques in Crowdsourcing

Nguyen Tai Hung

Lecture Notes in Computer Science, 2013

View PDFchevron_right

Reliable Aggregation of Boolean Crowdsourced Tasks

Luca de Alfaro

2015

View PDFchevron_right

Optimality of Belief Propagation for Crowdsourced Classification

Sewoong Oh

ArXiv, 2016

View PDFchevron_right

Whose Vote Should Count More: Optimal Integration of Labels from Labelers of Unknown Expertise

Paul Ruvolo

Advances in Neural …, 2009

View PDFchevron_right

An Evidential Imprecise Answer Aggregation Approach Based on Worker Clustering

Imen Boukhris

Intelligent Data Engineering and Automated Learning – IDEAL 2019, 2019

View PDFchevron_right

Crowd Labeling: a survey

Jafar Muhammadi

2014

View PDFchevron_right

Optimal Inference in Crowdsourced Classification via Belief Propagation

Sewoong Oh

IEEE Transactions on Information Theory, 2018

View PDFchevron_right

A Novel Crowd-sourcing Inference Method

William Tang

2019

View PDFchevron_right

A Robust Consistency Model of Crowd Workers in Text Labeling Tasks

Majed AlRubaian

IEEE Access, 2020

View PDFchevron_right

Error rate analysis of labeling by Crowdsourcing

Hongwei Li

International conference on machine learning workshop on machine learning meets crowdsourcing, 2013

View PDFchevron_right

Approximating Wisdom of Crowds using K-RBMs

Abhay Gupta

arXiv (Cornell University), 2016

View PDFchevron_right

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

View PDFchevron_right

Learning From Noisy Singly-labeled Data

Zachary Lipton

ArXiv, 2018

View PDFchevron_right

Clustering Based Approach for Ground Truth Inference in Crowdsourced Data

Babatunde Sawyerr

FUOYE Journal of Engineering and Technology

View PDFchevron_right

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

Gita Sukthankar

View PDFchevron_right

Exploiting Heterogeneous Graph Neural Networks with Latent Worker/Task Correlation Information for Label Aggregation in Crowdsourcing

Fangli Xu

ACM Transactions on Knowledge Discovery from Data, 2022

View PDFchevron_right

Measuring the Expertise of Workers for Crowdsourcing Applications

Laetitia Gros

Advances in Knowledge Discovery and Management, 2019

View PDFchevron_right

Improving Quality of Crowdsourced Labels via Probabilistic Matrix Factorization

Matt Lease, HyunJoon Jung

26th AAAI Human Computation Workshop 2012

View PDFchevron_right

Crowdsourcing Utilizing Subgroup Structure of Latent Factor Modeling

Annie Qu

Journal of the American Statistical Association, 2023

View PDFchevron_right

Time-Sensitive Bayesian Information Aggregation for Crowdsourcing Systems

John Guiver

Journal of Artificial Intelligence Research, 2016

View PDFchevron_right

University of Glasgow (qirdcsuog) at TREC Crowdsourcing 2001: TurkRank - Network-based Worker Ranking in Crowdsourcing

Guido Zuccon

2011

View PDFchevron_right

Reducing Label Cost by Combining Feature Labels and Crowdsourcing

Lise Getoor

2011

View PDFchevron_right

University of glasgow (qirdcsuog) at TREC crowdsourcing 2011: TurkRank - Network-based worker ranking in crowdsourcing

Jesus Perez

NIST Special Publication, 2011

View PDFchevron_right

Exploiting Document Content for Efficient Aggregation of Crowdsourcing Votes

Martin Davtyan, Thomas Hofmann, Carsten Eickhoff

24th ACM International Conference on Information and Knowledge Management (CIKM)

View PDFchevron_right

Assessing the Reliability of Crowdsourced Labels via Twitter

Majed Muhammed Ali

2019

View PDFchevron_right

CROWDSOURCE LABELS Training Data

Cesar Torres

2012

View PDFchevron_right

Error Rate Bounds and Iterative Weighted Majority Voting for Crowdsourcing

Hongwei Li

View PDFchevron_right

Selection and Aggregation Techniques for Crowdsourced Semantic Annotation Task

Shammur Chowdhury, Arindam Ghosh

View PDFchevron_right

Vote Aggregation as a Clustering Problem

Abhay Gupta

arXiv: Learning, 2016

View PDFchevron_right