Home > Seminars > Jamie Macbeth - Crowdsourcing Deep Thoughts: Meeting the Challenges of In-depth Language Understanding Systems for Smarter Social Media

Jamie Macbeth - Crowdsourcing Deep Thoughts: Meeting the Challenges of In-depth Language Understanding Systems for Smarter Social Media

Start:

5/18/2017 at 3:30PM

End:

5/18/2017 at 4:45PM

Location:

125 DeBartolo

Host:

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Ronald Metoyer

Ronald Metoyer

VIEW FULL PROFILE Email: rmetoyer@nd.edu
Phone: 574-631-5893
Website: http://www.nd.edu/~rmetoyer/
Office: 325C Cushing

Affiliations

College of Engineering Assistant Dean of Diversity and Special Initiatives
Dr. Metoyer's research interests are broadly in the areas of human-computer interaction with an emphasis on information visualization and applications in the areas of health and wellness, education, intelligence analysis, and software engineering.
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Intelligent systems driven by natural language input are well-positioned to aid those who are intervening against cyberbullying and other abuses of social media.  However, the language processing problems posed by these situations appear to be "Google proof": algorithms that scrape Wikipedia or other large text corpora for surface-level language properties underperform on these tasks.  This talk will discuss work to build systems that understand natural language about social situations in depth in support of these applications.  Our approach is based on a traditional symbolic method that represents deep semantics as complex combinations of simple, primitive acts, but it also uses crowdsourcing to collect these commonsense knowledge structures in scalable and inexpensive ways.

Seminar Speaker:

Jamie Macbeth

Fairfield University

Jamie Macbeth is an assistant professor of computer science in the School of Engineering at Fairfield University.  He was previously a postdoctoral fellow at Clemson University and a postdoctoral research associate with CSAIL at MIT.  He holds a Ph.D. in Computer Science from the University of California, Los Angeles, an M.S. in Physics from Stanford University, and a B.S. in Physics from Brown University.  His broad research interests include human-computer interaction, natural language understanding, and human factors of software engineering.  He also develops interactive games and automated grading systems to support his teaching in computing and programming.  He is a member of ACM, IEEE, and AAAI.