"Representing and Extracting Abstract Plot Structures to Model human Narrative Understanding," Mark Finlayson, Research Scientist, MIT

 

"Representing and Extracting Abstract Plot Structures to Model human Narrative Understanding," Mark Finlayson, Research Scientist, MIT

Sage 4101

February 19, 2014 12:00 PM - 1:30 PM

Narrative structure is a ubiquitous and intriguing phenomenon. Recognizing narrative structure is a process of abstraction, usually from natural language, and thus embodies a skill that underlies many cognitive tasks.  I describe my research program for investigating in what ways people are sensitive to narrative structure, especially in their own cultural context.  I first describe new techniques for representing the "who does what to whom" of a narrative, a necessary step if we are to computationally model the cognitive processes involved.  Second, I describe recent experiments demonstrating that people are actually able to reliably identify explicit narrative structures in text.  Finally, I describe my technique for modeling the extraction of narrative structure from narratives: I compare my results to those produced by a human expert, and describe the next steps in the research plan for investigating whether people are differentially sensitive to narrative structures prevalent in their own cultures.

Dr. Mark Finlayson is a Research Scientist at the Computer Science and Artificial Intelligence Laboratory at MIT. His research focuses on representing, extracting, and using higher-order semantic patterns in natural language, especially with regard to narrative. He received the B.S.E from the University of Michigan in 1998, and the M.S. and Ph.D. from MIT in 2001 and 2012, respectively, all in Electrical Engineering and Computer Science.  He is general chair of the Computational Models of Narrative (CMN) Workshop series, now approaching its fifth meeting, and is lead guest editor of a special issue on Computational Models of Narrative, to be published by the Journal of Literary & Linguistic Computing in 2014.

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