Collaborative crowdsourcing with Crowd4U

Kosetsu Ikeda, Atsuyuki Morishima, Habibur Rahman, Senjuti Basu Roy, Saravanan Thirumuruganathan, Sihem Amer-Yahia, Gautam Das

Research output: Contribution to journalConference articlepeer-review

7 Scopus citations

Abstract

Collaborative crowdsourcing is an emerging paradigm where a set of workers, often with diverse and complementary skills, form groups and work together to complete complex tasks. While crowdsourcing has been used successfully in many applications, collaboration is essential for achieving a high quality outcome for a number of emerging applications such as text translation, citizen journalism and surveillance tasks. However, no crowdsourcing platform today enables the end-to-end deployment of collaborative tasks. We demonstrate Crowd4U, a volunteer-based system that enables the deployment of diverse crowdsourcing tasks with complex dataows, in a declarative manner. In addition to treating workers and tasks as rich entities, Crowd4U also provides an easy-to-use form-based task UI. Crowd4U implements worker-to-task assignment algorithms that are appropriate for each kind of task. Once workers are assigned to tasks, appropriate worker collaboration schemes are enforced in order to enable effective result coordination.

Original languageEnglish (US)
Pages (from-to)1497-1500
Number of pages4
JournalProceedings of the VLDB Endowment
Volume9
Issue number13
DOIs
StatePublished - 2015
Externally publishedYes
Event42nd International Conference on Very Large Data Bases, VLDB 2016 - New Delhi, India
Duration: Sep 5 2016Sep 9 2016

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • Computer Science(all)

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