Gac: A deep reinforcement learning model toward user incentivization in unknown social networks
In recent years, many applications have deployed incentive mechanisms to promote users'
attention and engagement. Most incentive mechanisms determine specific incentive values …
attention and engagement. Most incentive mechanisms determine specific incentive values …
The Dark Side of Recruitment in Crowdsourcing: Ethics and Transparency in Micro-Task Marketplaces
Micro-task crowdsourcing marketplaces like Figure Eight (F8) connect a large pool of
workers to employers through a single online platform, by aggregating multiple …
workers to employers through a single online platform, by aggregating multiple …
[PDF][PDF] The effects of autonomy and task meaning in algorithmic management of crowdwork
With the tremendous development of AI technologies, people will increasingly encounter
software algorithms that supervise their work. Algorithmic management is the term for AI that …
software algorithms that supervise their work. Algorithmic management is the term for AI that …
On dynamically pricing crowdsourcing tasks
Crowdsourcing techniques have been extensively explored in the past decade, including
task allocation, quality assessment, and so on. Most of professional crowdsourcing platforms …
task allocation, quality assessment, and so on. Most of professional crowdsourcing platforms …
A budget-limited mechanism for category-aware crowdsourcing of multiple-choice tasks
Y Luo, NR Jennings - Artificial Intelligence, 2021 - Elsevier
Crowdsourcing harnesses human effort to solve computer-hard problems such as photo
tagging, entity resolution and sentiment analysis. Such tasks often have different levels of …
tagging, entity resolution and sentiment analysis. Such tasks often have different levels of …
A clarity and fairness aware framework for selecting workers in competitive crowdsourcing tasks
SJ Bozorg Zadeh Razavi, H Amintoosi, M Allahbakhsh - Computing, 2024 - Springer
Crowdsourcing is a powerful technique for accomplishing tasks that are difficult for machines
but easy for humans. However, ensuring the quality of the workers who participate in the …
but easy for humans. However, ensuring the quality of the workers who participate in the …
Identifying influential users in unknown social networks for adaptive incentive allocation under budget restriction
In recent years, recommenze the social influence among users to enhance the effect of
incentivization. Through incentivizing influential users directly, their followers in the social …
incentivization. Through incentivizing influential users directly, their followers in the social …
Incentivizing Crowdsourcing Workers via Social Networks in Edge Computing
W Tang, R Chen, Z Zhang, S Guo - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Crowdsourcing has proven to be an effective approach for leveraging collective intelligence
to solve tasks. However, in edge computing environments, crowdsourcing platforms often …
to solve tasks. However, in edge computing environments, crowdsourcing platforms often …
Cost-effective crowdsourced join queries for entity resolution without prior knowledge
B Yin, W Zeng, X Wei - Future Generation Computer Systems, 2022 - Elsevier
The join query, which finds matching pairs from two object sets, is a fundamental operation
in computer systems and helps to solve many real problems, eg, entity resolution. In this …
in computer systems and helps to solve many real problems, eg, entity resolution. In this …
REFORM: reputation based fair and temporal reward framework for crowdsourcing
Crowdsourcing is an effective method to collect data by employing distributed human
population. Researchers introduce appropriate reward mechanisms to incentivize agents to …
population. Researchers introduce appropriate reward mechanisms to incentivize agents to …