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CIDR
2011

Crowdsourced Databases: Query Processing with People

12 years 7 months ago
Crowdsourced Databases: Query Processing with People
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, combining two sets of images to identify people which appear in both, or extracting sentiment from a corpus of text snippets. Designing a workflow of various kinds of HITs for filtering, 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 workflows, allowing MTurk-style processing of relational databases. We describe a number of query execution and optimization challenges, and discuss some potential solutions.
Adam Marcus 0002, Eugene Wu 0002, Samuel Madden, R
Added 25 Aug 2011
Updated 25 Aug 2011
Type Journal
Year 2011
Where CIDR
Authors Adam Marcus 0002, Eugene Wu 0002, Samuel Madden, Robert C. Miller
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