Research Article
Knowledge Graphs Meet Crowdsourcing: A Brief Survey
@INPROCEEDINGS{10.1007/978-3-030-69992-5_1, author={Meilin Cao and Jing Zhang and Sunyue Xu and Zijian Ying}, title={Knowledge Graphs Meet Crowdsourcing: A Brief Survey}, proceedings={Cloud Computing. 10th EAI International Conference, CloudComp 2020, Qufu, China, December 11-12, 2020, Proceedings}, proceedings_a={CLOUDCOMP}, year={2021}, month={2}, keywords={Crowdsourcing Human computation Knowledge graphs Knowledge mining Ontology construction}, doi={10.1007/978-3-030-69992-5_1} }- Meilin Cao
Jing Zhang
Sunyue Xu
Zijian Ying
Year: 2021
Knowledge Graphs Meet Crowdsourcing: A Brief Survey
CLOUDCOMP
Springer
DOI: 10.1007/978-3-030-69992-5_1
Abstract
In recent years, as a new solution for hiring laborers to complete tasks, crowdsourcing has received universal concern in both academia and industry, which has been widely used in many IT domains such as machine learning, computer vision, information retrieval, software engineering, and so on. The emergence of crowdsourcing undoubtedly facilitates the Knowledge Graph (KG) technology. As an important branch of artificial intelligence that is recently fast developing, the KG technology usually involves machine intelligence and human intelligence, especially in the creation of knowledge graphs, human participation is indispensable, which provides a good scenario for the application of crowdsourcing. This paper first briefly reviews some basic concepts of knowledge-intensive crowdsourcing and knowledge graphs. Then, it discusses three key issues on knowledge-intensive crowdsourcing from the perspectives of task type, selection of workers, and crowdsourcing processes. Finally, it focuses on the construction of knowledge graphs, introducing innovative applications and methods that utilize crowdsourcing.
