Demonstration of Qurk: A Query Processor for Human Operators
Name
Karger_Demonstration of Qurk.pdf
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532.17 KB
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Author(s)
Marcus, Adam
Wu, Eugene
Karger, David R.
Madden, Samuel R.
Miller, Robert C.
Date Issued
June 2011
Journal
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data (SIGMOD '11)
Publisher
Association for Computing Machinery (ACM)
Citation
Adam Marcus, Eugene Wu, David R. Karger, Samuel Madden, and Robert C. Miller. 2011. Demonstration of Qurk: a query processor for humanoperators. In Proceedings of the 2011 ACM SIGMOD International Conference on Management of data (SIGMOD '11). ACM, New York, NY, USA, 1315-1318.
Version
Author's final manuscript
Abstract
Crowdsourcing technologies such as Amazon's Mechanical Turk ("MTurk") service have exploded in popularity in recent years. These services are increasingly used for complex human-reliant data processing tasks, such as labelling a collection of images, combining two sets of images to identify people that appear in both, or extracting sentiment from a corpus of text snippets. There are several challenges in designing a workflow that filters, aggregates, sorts and joins human-generated data sources. Currently, crowdsourcing-based workflows are hand-built, resulting in increasingly complex programs. Additionally, developers must hand-optimize tradeoffs among monetary cost, accuracy, and time to completion of results. These challenges are well-suited to a declarative query interface that allows developers to describe their worflow at a high level and automatically optimizes workflow and tuning parameters. In this demonstration, we will present Qurk, a novel query system that allows human-based processing for relational databases. The audience will interact with the system to build queries and monitor their progress. The audience will also see Qurk from an MTurk user's perspective, and complete several tasks to better understand how a query is processed.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike 3.0
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/1989323.1989486
