Work

Online Worker Scheduling for Maximizing Long-Term Utility in Crowdsourcing with Unknown Quality

Year: 2024

Type: article

Source: ACM Transactions on Internet Technology

DOI: 10.1145/3708893

Authors: Jiajun Wang, Pengfei Lin, Xingjian Ding, Jianxiong Guo, Zhiqing Tang, Deying Li, Weili Wu

Institutions: Beijing University of Technology, Beijing Normal-Hong Kong Baptist University, Beijing Normal University, Zhuhai, Renmin University of China, The University of Texas at Dallas

Language: English

Topic: Mobile Crowdsensing and Crowdsourcing

Subfield: Computer Science Applications

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

Funders: National Science Foundation, Hong Kong Baptist University, National Natural Science Foundation of China, Beijing Normal University

Awards: G4487702058, G5381427449, G6661371309, G6663045055, SPX: Collaborative Research: Enabling Efficient Computer Architectural and System Support for Next-Generation Network Function Virtualization, III: Small: Collaborative Research: Stream-Based Active Mining at Scale: Non-Linear Non-Submodular Maximization

OpenAlex ID: W4405546972

FWCI: 1.536

Cites: 43

Cited by: 4

Related to: 10