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Task assignment optimization in knowledge-intensive crowdsourcing
Basu Roy S., Lykourentzou I., Thirumuruganathan S., Amer-Yahia S., Das G. The VLDB Journal: The International Journal on Very Large Data Bases24 (4):467-491,2015.Type:Article
Date Reviewed: Dec 11 2015

This paper proposes work on “knowledge-intensive crowdsourcing (KI-C), which focuses on knowledge production rather than on the accomplishment of simple human tasks.” The authors deal with the problem of worker-to-task assignment, where a task is a piece of knowledge to provide.

The major contribution is definitively the model of the problem itself, which has been formulated as an optimization problem, taking into account human factors such as “worker expertise, wage requirements, and availability inside the optimization process.”

The approach proposed is evaluated “in terms of feasibility and quality” through a set of experiments that show that algorithms can lead workers to an increased knowledge production. The issues are extensively discussed in the paper and involve the complex relationship between human factors and collaboration.

I enjoyed reading this solid contribution, which can serve as a basis for further research as well as inspiration for other related works.

Reviewer:  Salvatore Pileggi Review #: CR144013 (1602-0132)
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