AI Seminar
February 10, 2003

Speaker: Tom O'Hara

Title:  Classifying functional relations in Factotum
                via WordNet hypernym associations

Abstract:
This talk the automatic classification of the functional relations in
the Factotum knowledge base via a statistical machine learning
algorithm. This incorporates a method for inferring prepositional
relation indicators from corpus data. It also uses lexical collocations
(i.e., word associations) and class-based collocations based on the
WordNet hypernym relations (i.e., is-subset-of). The result shows
substantial improvement over a baseline approach.

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Paper information:

Title:  Classifying functional relations in Factotum
                via WordNet hypernym associations

Authors:  Tom O'Hara and Janyce Wiebe

Publication: to appear in Proc. 4th Intl. Conference on Intelligent Text
                 Processing and Computational Linguistics  (CICLing-03),
                 February 17-22, 2003, CIC, IPN, Mexico City (c) Springer-Verlag

URL:
www.cs.nmsu.edu/~tomohara/ohara-factotum-roles-cicling03.pdf