Optimization Techniques for Human Computation-enabled Data Processing Systems
Speaker: Adam Marcus, CSAIL
Date: Thursday, June 14 2012
Time: 2:00PM to 3:00PM
Refreshments: 1:45PM
Location: 32-D463 (Star)
Host: Samuel Madden, CSAIL
Contact: Sheila Marian, x3-1996, sheila@csail.mit.edu
Thesis Defense Abstract:
Crowdsourced labor markets make it possible to recruit large numbers
of people to complete small tasks that are difficult to automate on
computers. These marketplaces are increasingly widely used, with
projections of over $1 billion being transferred between crowd
employers and crowd workers by the end of 2012. While crowdsourcing
enables forms of computation that artificial intelligence has not yet
achieved, it also presents crowd workflow designers with a series of
challenges including describing tasks, pricing tasks, identifying and
rewarding worker quality, dealing with incorrect responses, and
integrating human computation into traditional programming frameworks.
In this dissertation, we describe a system called Qurk that utilizes
techniques from databases such as declarative workflow defintion,
high-latency workflow execution, and query optimization to aid
crowd-powered workflow developers. We study how crowdsourcing can
enhance the capabilities of traditional databases by evaluating how to
implement basic database operators such as sorts and joins on datasets
that could not have been processed using traditional computation
frameworks. Finally, we explore the symbiotic relationship between
the crowd and query optimization, enlisting crowd workers to perform
selectivity estimation, a key component in optimizing complex
crowd-powered workflows.
See other events happening in June 2012
