Broad Area Colloquium For AI-Geometry-Graphics-Robotics-Vision
Natural Language Understanding: Word Spaces, Meaning,
Structure, Psychological Reality, Grammaticality
Christopher Manning
Computer Science Department
Stanford University
Wednesday, February 16, 2000
refreshments 4:05PM, talk begins 4:15PM
TCseq201, Lecture Hall B
http://robotics.stanford.edu/ba-colloquium/
Abstract
In recent years, statistical techniques based on collecting data from
large language corpora have transformed natural language processing --
just as many other areas of AI -- and statistical systems are yielding
better and still improving levels of task performance. In this talk I
will pick out and examine some of what can be done so successfully
with statistical models, from the treatment of words to sentence
parsing, but equally try to connect this work to issues of meaning,
representation, psycholinguistic plausibility, grammaticality, and
progress in achieving artificial intelligence.
About the Speaker
Christopher Manning is an Assistant Professor of Computer Science and
Linguistics at Stanford University. His research interests include
probabilistic models of language and statistical natural language
processing, constraint-based theories of grammar (HPSG and LFG),
computational lexicography, and syntactic typology. He received his
Ph.D. in linguistics from Stanford University in 1995. From
1994-1996, he was on the faculty of the Computational Linguistics
Program at Carnegie Mellon University, and from 1996-1999 he was "back
home" at the University of Sydney, before returning to Stanford at the
start of this academic year. His most recent book is Foundations of
Statistical Natural Language Processing (MIT Press, 1999, with Hinrich
Schuetze).
bac-coordinators@cs.stanford.edu
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Last modified: Fri Jan 7 11:23:04 PST 2000