We present a new unsupervised learning technique for the discovery of temporal clusters in large data sets. Our method performs hierarchical decomposition of the data to find stru...
This paper describes a lexicon organized around systematic polysemy: a set of word senses that are related in systematic and predictable ways. The lexicon is derived by a fully au...
How can it be said that texts are "near" or "distant" from one another? Are different texts by a single author more similar than texts by different authors? To...
A large number of learning algorithms, for example, spectral clustering, kernel Principal Components Analysis and many manifold methods are based on estimating eigenvalues and eig...
Mapping to one-dimensional values and then using a onedimensional indexing method has been proposed as a way of indexing multi-dimensional data. Most previous related work uses th...