This paper provides a linguistic semantic analysis of time and aspect in natural languages. On the basis of topological concepts, notions are introduced like the basic aspectual op...
We review the history of modeling score distributions, focusing on the mixture of normal-exponential by investigating the theoretical as well as the empirical evidence supporting i...
We introduce tiered clustering, a mixture model capable of accounting for varying degrees of shared (context-independent) feature structure, and demonstrate its applicability to i...
This paper presents a machine learning approach to the study of translationese. The goal is to train a computer system to distinguish between translated and non-translated text, in...
Randomised techniques allow very big language models to be represented succinctly. However, being batch-based they are unsuitable for modelling an unbounded stream of language whi...