Title:
An Information-Theoretic Definition of Similarity
Authors with addresses:
Dekang Lin
Department of Computer Science, University of Manitoba
Winnipeg, Manitoba, Canada, R3T, 2N2
Abstract (250 word maximum):
Similarity is an important and widely used
concept. Previous definitions of similarity are tied to a particular
application or a form of knowledge representation. We present an
information-theoretic definition of similarity that is applicable as
long as there is a probabilistic model. We demonstrate how our
definition can be used to measure the similarity in a number of
different domains.
Keywords:
similarity, natural language learning
Email address of contact author:
lindek@cs.umanitoba.ca
Phone number of contact author:
(204) 474-9740