Abstract
Label aggregation is one of the key topics in crowdsourcing research. Most researchers make their efforts in modeling ability of users and difficulty of instances. In this paper, we consider label aggregation from the view of grouping instances. We assume instances are sampled from latent groups and they share the same true label with their corresponding groups. We construct a graphical model named InGroup(Instance Grouping model) to infer latent group assignment as well as true labels. The experimental results show the advantages of our model compared with baselines.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
