Truth Inference With a Deep Clustering-Based Aggregation Model

Truth Inference With a Deep Clustering-Based Aggregation Model

Traditional truth inference algorithms take multiple source labels as input and infer true labels for objects. Besides source labels, object features have been introduced in inference algorithms to achieve superior performance. A typical algorithm such as learning from crowds learns a classification...

Full description

Bibliographic Details
Main Authors: Li'ang Yin, Yunfei Liu, Weinan Zhang, Yong Yu
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Crowdsourcing
truth inference
clustering methods
neural networks
unsupervised learning
machine learning
Online Access:https://ieeexplore.ieee.org/document/8950460/

Internet

https://ieeexplore.ieee.org/document/8950460/

Similar Items