Abstract

Structural Health Monitoring is of major interest in many areas of structural mechanics. This paper presents a new approach based on the combination of dimensionality reduction and data-mining techniques able to differentiate damaged and undamaged regions in a given structure. [...]

Abstract

 

Les empreses catalanes es troben en un moment de canvi. Fins ara fa poc, per tenir èxit en el negoci un factor molt important eren les habilitats personals del gerent. Ara amb la facilitat d’accés a la informació, el gran volum de [...]

Abstract

This paper conceptualizes the term big data and describes its relevance in social research and journalistic practices. We explain large-scale text analysis techniques such as automated content analysis, data mining, machine learning, topic modeling, and sentiment analysis, which may [...]

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This paper addresses an aspect not yet investigated in Spanish political communication: the use of data mining systems and machine learning in the construction of political discourse. This text details the potential of Calisto software, which was designed and implemented by the Popular [...]

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This article describes and evaluates the application of the supervised sentiment analysis in political communication through a real-time classifier of political opinions in Spanish tweets using machine learning techniques, both on a local computer and using distributed computing for [...]

Abstract

A tour is provided of the features, possibilities, scientific, technical and technologies that are collected under the interdisciplinary umbrella of big data and web analytics from the point of view of its application in practice. A reflection is offered about the challenges, risks [...]

Abstract

 Massive data collection and analysis is at the heart of many business models today. New technologies allow for fine-grained recommendation systems that help companies make accurate market predictions while also providing clients with highly personalized services. Because of this, [...]

Abstract

Predictive models are essential in dam safety assessment. They have been traditionally based on simple statistical tools such as the hydrostatic-season-time (HST) model. These tools are [...]

Abstract

Predictive models are essential in dam safety assessment. Both deterministic and statistical models applied in the day-to-day practice have demonstrated to be useful, although they show [...]

Abstract

The advances in information and communication technologies led to a general trend towards the availability of more detailed information on dam behaviour. This allows applying advanced data‐based [...]