Sequence labeling with multiple annotators

DOI10.1007/S10994-013-5411-2zbMath1320.62149OpenAlexW2112511942WikidataQ61906214 ScholiaQ61906214MaRDI QIDQ2251473

Yanyan Li

Publication date: 14 July 2014

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10994-013-5411-2

zbMATH Keywords

latent variable modelscrowdsourcingexpectation maximizationconditional random fieldsmultiple annotators

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Point estimation (62F10) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (2)

Millionaire: a hint-guided approach for crowdsourcing ⋮ A joint Gaussian process model for active visual recognition with expertise estimation in crowdsourcing

Uses Software

• L-BFGS
• JIGSAW

Cites Work

• Unnamed Item
• On the limited memory BFGS method for large scale optimization
• An Introduction to Conditional Random Fields

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