TY - JOUR
T1 - Collaborative crowdsourcing with Crowd4U
AU - Ikeda, Kosetsu
AU - Morishima, Atsuyuki
AU - Rahman, Habibur
AU - Roy, Senjuti Basu
AU - Thirumuruganathan, Saravanan
AU - Amer-Yahia, Sihem
AU - Das, Gautam
N1 - Funding Information:
The authors are grateful to the contributors to Crowd4U (listed at http://crowd4u.org). This research was par-tially supported by the Grant-in-Aid for Scientific Research (#25240012) from MEXT, Japan. The work of Habibur Rahman and Gautam Das was partially supported by National Science Foundation under grant 1344152, Army Re-search Office under grant W911NF-15-1-0020 and a grant from Microsoft Research. The work of Sihem Amer-Yahia is supported by ANR-13-CORD-0020. Any findings, con-clusions, or recommendations expressed in this material are those of the authors and do not necessarily re ect the views of the sponsors listed above.
Publisher Copyright:
© 2016 VLDB.
PY - 2015
Y1 - 2015
N2 - 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.
AB - 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.
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U2 - 10.14778/3007263.3007293
DO - 10.14778/3007263.3007293
M3 - Conference article
AN - SCOPUS:85020392702
SN - 2150-8097
VL - 9
SP - 1497
EP - 1500
JO - Proceedings of the VLDB Endowment
JF - Proceedings of the VLDB Endowment
IS - 13
T2 - 42nd International Conference on Very Large Data Bases, VLDB 2016
Y2 - 5 September 2016 through 9 September 2016
ER -