UnCrowd 2014: DASFAA Workshop on
Uncertain and Crowdsourced Data

Bali, Indonesia, 21 April 2014

About UnCrowd 2014

Crowdsourcing systems, such as Amazon Mechanical Turk and CrowdFlower, utilize human power to perform difficult tasks, such as entity resolution, search, filtering, image matching, or clustering. The important issues of collecting and managing the large volume of data in these applications have attracted plenty of attention from the database community. Typically, data obtained from crowdsourcing platforms are to be considered as uncertain, because of various levels of quality obtained by crowd workers.

Uncertain data management has also received considerable attention in the data management community. Models, algorithms, systems, for fuzzy databases, probabilistic databases, or reasoning under incompleteness, have been proposed and numerous applications, from information integration to information extraction and data cleaning, have been identified. The objective of this workshop is to explore the connection between uncertain data management and crowdsourcing. How can the crowd reduce uncertainty in data obtained from automatic processes, such as schema matching or machine learning? How can uncertain data management techniques be applied to the modeling of the crowd?


2014-03-26: UnCrowd 2014 Program
The full program of UnCrowd 2014 is now available.
2013-09-18: Lei Chen keynote speaker
We are pleased to announce Lei Chen, Hong Kong University of Science and Technology, as the keynote speaker of the workshop.
2013-09-17: UnCrowd 2014, a DASFAA 2014 Workshop
The DASFAA Workshop on Uncertain and Crowdsourced Data has been accepted as a DASFAA 2014 workshop.

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