[Colloq] Time of Talk

[Nicole Bekerian]

Good Afternoon, 

My apologies, the talk will begin at 3:00 on Wednesday, November 9, 2011.





----- Original Message -----
From: "Nicole Bekerian" <nicoleb at zimbra.ccs.neu.edu>
To: "colloq" <colloq at lists.ccs.neu.edu>, "clinical-faculty" <clinical-faculty at lists.ccs.neu.edu>, "lecturers" <lecturers at lists.ccs.neu.edu>, "ResearchProfessors" <ResearchProfessors at lists.ccs.neu.edu>, "Doreen Hodgkin" <d.hodgkin at neu.edu>, co-opfaculty at lists.ccs.neu.edu
Sent: Wednesday, November 2, 2011 12:29:02 PM GMT -05:00 US/Canada Eastern
Subject: Talk: Crowdsourcing using Mechanical Turk: Quality Management and Scalability

The College of Computer and Information Science Presents:



Speaker: Prof. Panos G. Ipeirotis
Title:  Crowdsourcing using Mechanical Turk: Quality Management and Scalability
Date:  Wednesday, November 9, 2011 
Location:  366 WVH

On Wednesday, November 9, Prof. Panos G. Ipeirotis will visit our college to give a talk about his research. Panos is an Associate Professor and George A. Kellner Faculty Fellow at the Department of Information, Operations, and Management Sciences at Leonard N. Stern School of Business of New York University. His recent research interests focus on crowdsourcing and on mining user-generated content on the Internet. He received his Ph.D. degree in Computer Science from Columbia University in 2004, with distinction. He has received three "Best Paper" awards (IEEE ICDE 2005, ACM SIGMOD 2006, WWW 2011), two "Best Paper Runner Up" awards (JCDL 2002, ACM KDD 2008), and is also a recipient of a CAREER award from the National Science Foundation.

Abstract:
I will discuss the acquisition of "labels" for data items when the labeling is imperfect. Labels are values provided by humans for specified variables on data items, such as "PG-13" for "Adult Content Rating on this Web Page." With the increasing popularity of micro-outsourcing systems, such as Amazon's Mechanical Turk, it often is possible to obtain less-than-expert labeling at low cost. I will present strategies of managing quality in a crowdsourcing environment, showing in parallel how to integrate data acquisition with the process of learning machine learning models. I illustrate the results using real-life applications from on-line advertising: leveraging Mechanical Turk to help classify web pages as being objectionable to advertisers. Time permitting, I will also discuss our latest results showing that mice and Mechanical Turk workers are not that different after all.

Host: Mirek Riedewald


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Best, 
Nicole 

______________________________________________________________ 

Nicole Bekerian 
Administrative Assistant 

Northeastern University 
College of Computer and Information Science 
360 Huntington Ave. 
202 West Village H 
Boston, MA 02115 

Phone: 617.373.2462 
Fax: 617.373.5121 

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Best, 
Nicole 

______________________________________________________________ 

Nicole Bekerian 
Administrative Assistant 

Northeastern University 
College of Computer and Information Science 
360 Huntington Ave. 
202 West Village H 
Boston, MA 02115 

Phone: 617.373.2462 
Fax: 617.373.5121