@inproceedings{marcus2011crowdsourced,
  abstract = {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.},
  author = {Marcus, Adam and Wu, Eugene and Madden, Samuel and Miller, Robert C.},
  booktitle = {Proceedings of the 5th Biennial Conference on Innovative Data Systems Research},
  doi = {1721.1/62827},
  interhash = {b6b7d67c3c09259fb2d5df3f52e24c9d},
  intrahash = {29723ba38aa6039091769cd2f69a1514},
  month = jan,
  pages = {211--214},
  publisher = {CIDR},
  title = {Crowdsourced Databases: Query Processing with People},
  url = {http://dspace.mit.edu/handle/1721.1/62827},
  year = 2011
}