Word space models, in the sense of vector space models built on distributional data taken from texts, are used to model semantic relations between words. We argue that the high dim...
More and more documents on the World Wide Web are based on templates. On a technical level this causes those documents to have a quite similar source code and DOM tree structure. G...
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
The recent advances in the research of left-continuous t-norms is summarized in this talk. The main focus is on construction methods, geometric description, and structural charact...
Bayesian graphical models are commonly used to build student models from data. A number of standard algorithms are available to train Bayesian models from student skills assessment...
Michel C. Desmarais, Alejandro Villarreal, Michel ...