AI Seminar
February 3, 2003

Speaker: Tom O'Hara

Title: Inducing criteria for mass noun lexical mappings using the Cyc KB, and its extension to WordNet
 

Abstract:
This talk discusses an automatic approach for learning semantic criteria
for the mass versus count noun distinction by induction over the lexical
mappings contained in the Cyc knowledge base. This produces accurate
results (89.5%) using a decision tree that only incorporates semantic
features (i.e., Cyc ontological types). Comparable results (86.9%) are
obtained using OpenCyc, the publicly available version of Cyc. For
broader applicability, the mass noun criteria using Cyc are converted
into criteria using WordNet, preserving the general accuracy (86.3%).

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Paper information:

Title:  Inducing criteria for mass noun lexical mappings using the Cyc
KB, and its extension to WordNet

Authors:  Tom O'Hara, Nancy Salay, Michael Witbrock, Dave
Schneider, Bjørn Aldag, Stefano Bertolo, Kathy Panton, Fritz
Lehmann, Jon Curtis, Matt Smith, David Baxter, and Peter Wagner

Publication: in Proc. 5th International Workshop on Computational
Semantics (IWCS-5), Tilburg, January 14-16, 2003.

URL:
www.cs.nmsu.edu/~tomohara/ohara-speech-part-inference-iwcs03.pdf