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### Begin Citation ### Do not delete this line ###
%R 98-05
%U /ftp/pub/WWW/faculty/rapaport/Papers/krnlp.tr.ps
%A Rapaport, William J.
%A Ehrlich, Karen
%T A Computational Theory of Vocabulary Acquisition
%D April 14, 1998
%I Department of Computer Science, SUNY Buffalo
%K computational linguistics, vocabulary acquisition, machine learning
%X As part of an interdisciplinary project to develop a computational 
cognitive model of a reader of narrative text, we are developing a 
computational theory of how natural-language-understanding systems can 
automatically acquire new vocabulary by determining from context  the 
meaning of words that are unknown, misunderstood, or used in a new 
sense.  `Context' includes surrounding text, grammatical information, 
and background knowledge, but no external sources.  Our thesis is that 
the meaning of such a word  *can* be determined from context, can be 
*revised* upon further encounters with the word, ``*converges*'' to a 
dictionary-like definition if enough context has been provided and 
there have been enough exposures to the word, and eventually ``*settles 
down*'' to a ``steady state'' that is always subject to revision upon 
further encounters with the word.  The system is being implemented in 
the SNePS knowledge-representation and reasoning system. 
This essay is forthcoming as a chapter in Iwanska, Lucja, & Shapiro, 
Stuart C. (1999), _Natural Language Processing and Knowledge 
Representation: Language for Knowledge and Knowledge for Language_ 
(Menlo Park, CA/Cambridge, MA:  AAAI Press/MIT Press).