This paper presents the Topic-Aspect Model (TAM), a Bayesian mixture model which jointly discovers topics and aspects. We broadly define an aspect of a document as a characteristi...
In this paper, we present an efficient algorithm for 3D object recognition in presence of clutter and occlusions in noisy, sparse and unsegmented range data. The method uses a robu...
This work addresses the use of computational linguistic analysis techniques for conceptual graphs learning from unstructured texts. A technique including both content mining and i...
This paper describes how to extract stock quote data and display it with a dynamic update (using free, but delayed data streams). As a part of the architecture of the program, we ...
This paper proposes an original model of the execution time of assembly instructions in superscalar architectures. The approach is based on a rigorous mathematical model and provi...
William Fornaciari, Vito Trianni, Carlo Brandolese...