Finding and Extracting Opinions on the Web
, October 14, 2008, Lecture Hall 1
Fall 2008 PLATO Royalty Lecture Series
The accurate identification and interpretation of opinions is a critical step toward
ing the subjective language that comprises editorials, blogs, reviews (of products,
movies, books), chat room dialogues, and even (purportedly factual) newspaper articles. This
talk will explain one approach for identifying and
summarizing opinions in on
Claire Cardie is a Professor in the Computer Science department at Cornell University,
where she is also the Charles and Barbara Weiss Director of the university's new Information
Science program. She obtained a B.S. in Computer
Science from Yale University (1982) and an
M.S. and PhD in Computer Science at the University of Massachusetts at Amherst (1994).
Cardie's research is in the areas of natural language processing and machine learning. In
particular, she has focused on the
development of machine learning techniques for building
robust and portable information extraction systems. She is a recipient of a National Science
Foundation CAREER award, has served two elected terms as secretary of the North American
chapter of the As
sociation for Computational Linguistics (NAACL) (2000
2003), and is
currently a member of the ACL's executive committee. She has been Program Chair for the
joint ACL/COLING conference in 2006, for CoNLL (Conference on Natural Language
Learning) in 2000, an
d for the EMNLP (Empirical Methods in NLP) conference in 1997.
Cardie has served as associate/action editor for JAIR (Journal of AI Research) and JMLR
(Journal of Machine Learning Research), and as an editorial board member for the Machine
l and Computational Linguistics.
This Lecture Series is sponsored by Evergreen’s PLATO Royalty Fund, a fund established with royalties
from computer assisted instruction (CAI) software written by Evergreen faculty John Aikin Cushing and
students in the
early 1980’s for the Control Data PLATO system.