The introduction of digital data sources has positively impacted public health surveillance and has paved the way for novel approaches. Internet-based sources provide large volumes of data which can be analysed in near ...

Terminological resources have proven necessary in many organizations and institutions to ensure communication between experts. However, the maintenance of these resources is a very time-consuming and expensive process. ...

Recently, machine translation has demonstrated significant progress in terms of translation quality. However, most of the research has focused on translating with pure monolingual texts in the source and the target side ...

While the recognition of positive/negative sentiment in text is an established task with many standard data sets and well developed methodologies, the recognition of a more nuanced affect has received less attention: there ...

Sentiments and beliefs play an important role in actions and decisions in a market environment; for example, people disliking a brand will tend to avoid products of it or people aiming to reduce their carbon-dioxide footprint ...

Social media are interactive platforms that facilitate the creation or sharing of information, ideas or other forms of expression among people. This exchange is not free from offensive, trolling or malicious contents ...

This paper describes steps that have been taken to construct a development dataset for the task of Technology Structure Mining. We have defined the proposed task as the process of mapping a scientific corpus into a ...

Extracting general or intermediate level terms is a relevant problem that has not received much attention in literature. Current approaches for term extraction rely on contrastive corpora to identify domain-specific terms, ...

In this paper, we address the problem of extracting and integrating bilingual terminology into a Statistical Machine Translation (SMT) system for a Computer Aided Translation (CAT) tool scenario. We develop a framework ...