  This paper (cmp-lg/yymmnnn) has been accepted for publication in the student
session of EACL-95. It outlines ongoing work using statistical and unsupervised
neural network methods for clustering words in untagged corpora. Such
approaches are of interest when attempting to understand the development of
human intuitive categorization of language as well as for trying to improve
computational methods in natural language understanding. Some preliminary
results using a simple statistical approach are described, along with work
using an unsupervised neural network to distinguish between the sense classes
into which words fall.
