University of Trento

About: University of Trento is a education organization based out in Trento, Italy. It is known for research contribution in the topics: Population & Context (language use). The organization has 10527 authors who have published 30978 publications receiving 896614 citations. The organization is also known as: Universitá degli Studi di Trento & Universita degli Studi di Trento.

World-trade web: Topological properties, dynamics, and evolution

Abstract: This paper studies the statistical properties of the web of import-export relationships among world countries using a weighted-network approach. We analyze how the distributions of the most important network statistics measuring connectivity, assortativity, clustering, and centrality have coevolved over time. We show that all node-statistic distributions and their correlation structure have remained surprisingly stable in the last 20 years—and are likely to do so in the future. Conversely, the distribution of positive link weights is slowly moving from a log-normal density towards a power law. We also characterize the autoregressive properties of network-statistics dynamics. We find that network-statistics growth rates are well-proxied by fat-tailed densities like the Laplace or the asymmetric exponential power. Finally, we find that all our results are reasonably robust to a few alternative, economically meaningful, weighting schemes.

Dimensions of "uniquely" and "non-uniquely" human emotions.

Abstract: Emotion scientists often distinguish those emotions that are encountered universally, even among animals ("primary emotions"), from those experienced by human beings ("secondary emotions"). No attempt, however, has ever been made to capture the lay conception about this distinction and to find the criteria on which the distinction is based. The first study presented in this paper was conducted in three countries involving four languages, so as to allow for cross-cultural comparisons. Results showed a remarkable convergence. People from all samples not only differentiated between "uniquely human" and "non-uniquely human" emotions on a continuum, but they did so on the same basis as the one used by emotion scientists to distinguish between "primary" and "secondary" emotions. Study 2 focused on the implicit use of such a distinction. When confronted with a human (animal) context, participants reacted faster to secondary (vs primary) emotions. The implications of the human uniqueness of some emotions within the social and interpersonal contexts are discussed.

Semantic matching: algorithms and implementation

Abstract: We view match as an operator that takes two graph-like structures (e.g., classifications, XML schemas) and produces a mapping between the nodes of these graphs that correspond semantically to each other. Semantic matching is based on two ideas: (i) we discover mappings by computing semantic relations (e.g., equivalence, more general); (ii) we determine semantic relations by analyzing the meaning (concepts, not labels) which is codified in the elements and the structures of schemas. In this paper we present basic and optimized algorithms for semantic matching, and we discuss their implementation within the S-Match system. We evaluate S-Match against three state of the art matching systems, thereby justifying empirically the strength of our approach.