Machine learning with crowdsourcing: A brief summary of the past research and future directions
With crowdsourcing systems, labels can be obtained with low cost, which facilitates the
creation of training sets for prediction model learning. However, the labels obtained from …
creation of training sets for prediction model learning. However, the labels obtained from …
Knowledge learning with crowdsourcing: A brief review and systematic perspective
J Zhang - IEEE/CAA Journal of Automatica Sinica, 2022 - ieeexplore.ieee.org
Big data have the characteristics of enormous volume, high velocity, diversity, value-sparsity,
and uncertainty, which lead the knowledge learning from them full of challenges. With the …
and uncertainty, which lead the knowledge learning from them full of challenges. With the …
Declare: Debunking fake news and false claims using evidence-aware deep learning
Misinformation such as fake news is one of the big challenges of our society. Research on
automated fact-checking has proposed methods based on supervised learning, but these …
automated fact-checking has proposed methods based on supervised learning, but these …
Truth inference in crowdsourcing: Is the problem solved?
Crowdsourcing has emerged as a novel problem-solving paradigm, which facilitates
addressing problems that are hard for computers, eg, entity resolution and sentiment …
addressing problems that are hard for computers, eg, entity resolution and sentiment …
A survey on truth discovery
Thanks to information explosion, data for the objects of interest can be collected from
increasingly more sources. However, for the same object, there usually exist conflicts among …
increasingly more sources. However, for the same object, there usually exist conflicts among …
Where the truth lies: Explaining the credibility of emerging claims on the web and social media
The web is a huge source of valuable information. However, in recent times, there is an
increasing trend towards false claims in social media, other web-sources, and even in news …
increasing trend towards false claims in social media, other web-sources, and even in news …
Quality of information aware incentive mechanisms for mobile crowd sensing systems
Recent years have witnessed the emergence of mobile crowd sensing (MCS) systems,
which leverage the public crowd equipped with various mobile devices for large scale …
which leverage the public crowd equipped with various mobile devices for large scale …
Deep reinforcement learning for partially observable data poisoning attack in crowdsensing systems
M Li, Y Sun, H Lu, S Maharjan… - IEEE Internet of Things …, 2019 - ieeexplore.ieee.org
Crowdsensing systems collect various types of data from sensors embedded on mobile
devices owned by individuals. These individuals are commonly referred to as workers that …
devices owned by individuals. These individuals are commonly referred to as workers that …
Making better use of the crowd: How crowdsourcing can advance machine learning research
JW Vaughan - Journal of Machine Learning Research, 2018 - jmlr.org
This survey provides a comprehensive overview of the landscape of crowdsourcing
research, targeted at the machine learning community. We begin with an overview of the …
research, targeted at the machine learning community. We begin with an overview of the …
Faitcrowd: Fine grained truth discovery for crowdsourced data aggregation
In crowdsourced data aggregation task, there exist conflicts in the answers provided by large
numbers of sources on the same set of questions. The most important challenge for this task …
numbers of sources on the same set of questions. The most important challenge for this task …