Different from familiar clustering objects, text documents have sparse data spaces. A common way of representing a document is as a bag of its component words, but the semantic re...
We present a technique for augmenting annotated training data with hierarchical word clusters that are automatically derived from a large unannotated corpus. Cluster membership is...
: The proposed divisive clustering method performs simultaneously a hierarchy of a set of objects and a monothetic characterization of each cluster of the hierarchy. A division is ...
The paper deals with the linguistic problem of fully automatic grouping of semantically related words. We discuss the measures of semantic relatedness of basic word forms and descr...
This paper studies an adaptive clustering problem. We focus on re-clustering an object set, previously clustered, when the feature set characterizing the objects increases. We prop...