In this paper we provide a foundation of a theory of contextual reasoning from the perspective of a theory of knowledge representation. Starting from the so-called metaphor of the...
Massimo Benerecetti, Paolo Bouquet, Chiara Ghidini
We introduce, analyze and demonstrate a recursive hierarchical generalization of the widely used hidden Markov models, which we name Hierarchical Hidden Markov Models (HHMM). Our m...
Abstract Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. A...
We present an analogy between the operation of a Wireless Sensor Network and the sampling and reconstruction of a signal. We measure the impact of three factors on the quality of ...
This work presents a general rank-learning framework for passage ranking within Question Answering (QA) systems using linguistic and semantic features. The framework enables query...
Matthew W. Bilotti, Jonathan L. Elsas, Jaime G. Ca...