Some machine learning applications are intended to learn properties of data sets where the correct answers are not already known to human users. It is challenging to test such ML ...
The manipulation of large-scale document data sets often involves the processing of a wealth of features that correspond with the available terms in the document space. The employm...
We present a tutorial survey on some recent approaches to unsupervised machine learning in the context of statistical pattern recognition. In statistical PR, there are two classica...
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...
In this paper, we give an overview of a system (CAIMAN) that can facilitate the exchange of relevant documents between geographically dispersed people in Communities of Interest. ...