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Talks & Seminars
Title: Human-Powered Data Management
Aditya Parameswaran, MIT CSAIL and Microsoft Research New England, soon-to-be (starting June 2014) Assistant Professor in Computer Science at the University of Illinois, Urbana-Champaign (UIUC)
Date & Time: December 6, 2013 11:30
Venue: CSE Conf Room
Abstract:
Fully automated algorithms are inadequate for a number of data analysis tasks, especially those involving images, video, or text. Thus, there is a need to combine “human computation” (or crowdsourcing), together with traditional computation, in order to improve the process of understanding and analyzing data. I have addressed several topics in the general area of human-powered data management. I design algorithms and systems for combining human and traditional computation for: (a) data processing, e.g., using humans to help sort, cluster, or clean data; (b) data extraction, e.g., having humans help create structured data from information in unstructured web pages; and (c) data gathering, i.e., asking humans to provide data that they know about or can locate, but that would be difficult to gather automatically. My focus in all of these areas is to find solutions that expend as few resources as possible (e.g., time waiting, human effort, or money spent), while still providing high quality results. In this talk, I will first present a broad perspective of our research on human-powered data management, and I will describe some systems and applications that have motivated our research. I will then present details of one of the problems we have addressed: filtering large data sets with the aid of humans. Finally, I will argue that human-powered data management is an area in its infancy, by describing a number of open problems.
Speaker Profile:
Aditya Parameswaran is a soon-to-be (starting June 2014) Assistant Professor in Computer Science at the University of Illinois, Urbana-Champaign (UIUC). He is currently spending the year visiting MIT CSAIL and Microsoft Research New England, after completing his Ph.D. from Stanford University in September 2013, advised by Prof. Hector Garcia-Molina. He is broadly interested in data analytics and management, with research results in human computation, visual analytics, information extraction and integration, and recommendation systems. Aditya is a recipient of the Arthur Samuel award for the best dissertation in Computer Science at Stanford University (2013), the Key Scientific Challenges Award from Yahoo! Research (2010), two best-of-conference citations (VLDB 2010 and KDD 2012), the Terry Groswith graduate fellowship at Stanford University (2007), and the Gold Medal in Computer Science at IIT Bombay (2007).
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