The automated evaluation of inferred word classifications
John Hughes, Eric Atwell · White Rose Research Online (University of Leeds, The University of Sheffield, University of York) · 1994
. Although automatically inferring classifications of words has been attempted by many researchers recently, no formal attempts to evaluate their results were made. Instead they relied on a looks good to me intuitive self-evaluation. We outline a method by which automated word classification techniques can be fairly compared. The process by which words are automatically grouped into classes involves a number of decision points. The experiments selected a set of options for many of the decision points and rated each combination of the factors so that the most successful approach can be found. We directly compare some of the adopted approaches of other researchers with the set of factors that were found to produce the most linguistically plausible classification in our experiments. The evaluation method is also shown to be a valuable aid to highlighting approaches that are inefficient. 1 Hierarchical Clustering to Cluster Words Hierarchical clustering is a way to produce a taxonomic cl...