EmotiBlog: a finer-grained and more precise learning of subjectivity expression models

The exponential growth of the subjective information in the framework of the Web 2.0 has led to the need to create Natural Language Processing tools able to analyse and process such data for multiple practical applications. They require training on specifically annotated corpora, whose level of detail must be fine enough to capture the phenomena involved. This paper presents EmotiBlog – a fine-grained annotation scheme for subjectivity. We show the manner in which it is built and demonstrate the benefits it brings to the systems using it for training, through the experiments we carried out on opinion mining and emotion detection. We employ corpora of different textual genres –a set of annotated reported speech extracted from news articles, the set of news titles annotated with polarity and emotion from the SemEval 2007 (Task 14) and ISEAR, a corpus of real-life self-expressed emotion. We also show how the model built from the EmotiBlog annotations can be enhanced with external resources. The results demonstrate that EmotiBlog, through its structure and annotation paradigm, offers high quality training data for systems dealing both with opinion mining, as well as emotion detection.

Incorporating global positioning data in real time P2P audio/video streams for mobile devices

We propose an original method to geoposition an audio/video stream with multiple emitters that are at the same time receivers of the mixed signal. The achieved method is suitable for those comes where a list of positions within a designated area is encoded with a degree of precision adjusted to the visualization capabilities; and is also easily extensible to support new requirements. This method extends a previously proposed protocol, without incurring in any performance penalty.

P2P audio/video protocol with global positioning data in real time for mobile devices

In this paper, we propose an original method to geoposition an audio/video stream with multiple emitters that are at the same time receivers of the mixed signal. The obtained method is suitable when a list of positions within a known area is encoded with precision tailored to the visualization capabilities of the target device. Nevertheless, it is easily adaptable to new precision requirements, as well as parameterized data precision. This method extends a previously proposed protocol, without incurring in any performance penalty.

Tasas de deformación GPS en la cuenca del Bajo Segura (Cordillera Bética oriental)

En este trabajo hemos cuantificado las tasas de deformación actual de la cuenca del Bajo Segura (NE del corredor de cizalla de la Bética oriental), a partir del análisis de una red GPS con 11 vértices geodésicos. Se han analizado los datos de cuatro campañas GPS entre junio de 1999 y enero de 2013, que han sido procesados con la versión 6.2 del software GIPSY-OASIS. Este software utiliza la técnica de posicionamiento puntual de precisión conocido por las siglas PPP. Se observa un acortamiento ~N-S en toda la cuenca de mayor magnitud en el sur, en la zona de falla del Bajo Segura, con valores que varían de oeste a este entre 0,73 y 0,24 mm/año. En el borde septentrional de la cuenca, en la zona de falla de Crevillente, los valores de acortamiento N-S son menores. Sin embargo, en esta falla se ha observado un movimiento lateral sinistrorso que, en la componente E-O, varía entre 0,44 y 0,75 mm/año.