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%0 Conference Proceedings
%A Marcus, Adam; Wu, Eugene; Madden, Samuel & Miller, Robert C.
%D 2011
%T Crowdsourced Databases: Query Processing with People
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%B Proceedings of the 5th Biennial Conference on Innovative Data Systems Research
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%I CIDR
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%6
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%P 211--214
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%8 January
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%3 inproceedings
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%F marcus2011crowdsourced
%K database, crowdsourcing, intelligence, social, computing, cirg, collective, query
%X Amazon's Mechanical Turk (\MTurk") service allows users to post short tasks (\HITs") that other users can receive a small amount of money for completing. Common tasks on the system include labelling a collection of images, com- bining two sets of images to identify people which appear in both, or extracting sentiment from a corpus of text snippets. Designing a work ow of various kinds of HITs for ltering, aggregating, sorting, and joining data sources together is common, and comes with a set of challenges in optimizing the cost per HIT, the overall time to task completion, and the accuracy of MTurk results. We propose Qurk, a novel query system for managing these work ows, allowing crowd- powered processing of relational databases. We describe a number of query execution and optimization challenges, and discuss some potential solutions.
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%U http://dspace.mit.edu/handle/1721.1/62827
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