English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Crowdsourcing enables one to leverage on the intelligence and wisdom ofpotentially large groups of individuals toward solving problems. Commonproblems approached with crowdsourcing are labeling images, translating ortranscribing text, providing opinions or ideas, and similar - all tasks thatcomputers are not good at or where they may even fail altogether. Theintroduction of humans into computations and/or everyday work, however, alsoposes critical, novel challenges in terms of quality control, as the crowd istypically composed of people with unknown and very diverse abilities, skills,interests, personal objectives and technological resources. This survey studiesquality in the context of crowdsourcing along several dimensions, so as todefine and characterize it and to understand the current state of the art.Specifically, this survey derives a quality model for crowdsourcing tasks,identifies the methods and techniques that can be used to assess the attributesof the model, and the actions and strategies that help prevent and mitigatequality problems. An analysis of how these features are supported by the stateof the art further identifies open issues and informs an outlook on hot futureresearch directions.

Quality Control in Crowdsourcing: A Survey of Quality Attributes, Assessment Techniques and Assurance Actions