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  • CS Colloquium: Vasilis Verroios (Stanford) - Combining Algorithms and Humans for Large-Scale Data Integration

    Wed, Feb 01, 2017 @ 11:00 AM - 12:20 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars

    Speaker: Vasilis Verroios , Stanford University

    Talk Title: Combining Algorithms and Humans for Large-Scale Data Integration

    Series: CS Colloquium

    Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.

    Modern enterprises collect data from their operations and the web, and strongly depend on the collected data to make important decisions. To analyze the collected data, enterprises need to first perform data integration, i.e., combine the data from the multiple sources to create a unified set.

    Data integration involves some tasks that are still very hard for computer algorithms, like tasks involving images, video, natural language, or data semantics understanding. Since humans may be more accurate with such tasks, the approach of crowdsourcing has been proposed and applied by large companies and research organizations, over the last years. In crowdsourcing, humans are also involved, in order to enhance computer algorithms by completing small tasks, like classifying a forum comment as offensive or ironic. Crowdsourcing drastically improves the accuracy of the outcome compared to using only computer algorithms, however, it does not scale due to the large amount of time (and monetary compensation) required by humans. In this talk, I will discuss how to make crowdsourcing scalable for data integration.

    Biography: Vasilis Verroios is a PhD candidate in the Computer Science Department, at Stanford University. His advisor is Hector Garcia-Molina. He received a B.S. and M.S. in Computer Science from the University of Athens, in 2006 and 2008, respectively. In the past, he has been a member of the "Management of Data, Information, & Knowledge Group" at the University of Athens, and he has worked for oDesk and Microsoft Research. His primary interests include data integration, data analytics, and data mining.

    Host: Cyrus Shahabi

    Location: Ronald Tutor Hall of Engineering (RTH) - 217

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair

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