Home > Events > CLIP Colloquium: Paul McNamee (Johns Hopkins University)
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CLIP Colloquium: Paul McNamee (Johns Hopkins University)

Time: 
Wednesday, December 07, 2016 - 11:00 AM to 12:00 PM
Location: 
3258 A.V. Williams Building

 

Machine Learning not Boolean Search: A Case Study in Public Health Informatics

Abstract: One recent estimate for the annual growth rate of scientific publications is 8% per year (Bornmann & Mutz, JAIST 2014), and in some discplines growth is even higher. This creates problems for scientific understanding: researchers and decision makers want to be informed by the best, most recent, and most reliable scientific data. One approach to address the rising amount of published literature is reliance on systematic reviews: meta reviews that comprehensively survey the extant literature and synthesize results from previously published studies.

This talk discusses the use of supervised text classification to partially automate the literature search process in systematic reviews. A systematic review is unlike most information retrieval applications because it is important to not only find documents that are useful (e.g., as in Web search), but to find the preponderance of documents that meet specified selection criteria. Similar "high recall" problems arise in patent application review and legal e-discovery. Some experimental results will be presented from a recent collaboration with the U.S. Centers for Disease Control and Prevention to identify scientific articles about methods to improve health care worker effectiveness in the developing world.

Bio: Paul McNamee is a member of the Principal Professional Staff at the Johns Hopkins University Applied Physics Laboratory and a Senior Research Scientist with the JHU Human Language Technology Center of Excellence.  Dr. McNamee earned a Ph.D. in computer science from the University of Maryland Baltimore County in 2008, where his dissertation research focused on innovative methods for effective multilingual text retrieval. He has published over 75 scholarly publications related to the automated processing of language data and he has participated in numerous international competitions for text retrieval technologies.