Pierpaolo Vittorini

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The eXtensible markup language (XML) is a metalanguage which is useful to represent and exchange data between heterogeneous systems. XML may enable healthcare practitioners to document, monitor, evaluate, and archive medical information and services into distributed computer environments. Therefore, the most recent proposals on electronic health records(More)
Text comprehension skills and strategies develop enormously from the age of 7-8 until the age of 11, when children advance as independent readers. Nowadays, more and more young children turn out to be poor (text) compre-henders: they demonstrate text comprehension difficulties, related to inference-making skills, despite proficiency in word decoding and(More)
TERENCE is an FP7 ICT European project that is developing an adaptive learning system for supporting poor comprehenders and their educators. Its learning material are books of stories and games. The so-called smart games serve to stimulate the story comprehension. This paper focuses on the analysis of flat stories with a specific annotation language and the(More)
To respond to the need for interoperable information systems in public health, several proposals based on XML-related technologies are currently available. For instance, the CDA [8] is an architecture developed by the HL7 organization for representing and managing clinical documents, while the PHIN [12] is a CDC infrastructure whose aim is to automatically(More)
Currently, large efforts are spent to develop standards and architectures useful to achieve more effective interoperability among medical information systems. Despite such efforts, there are no researches produced so far to directly analyse, with statistical methods, biomedical data represented as eXtensible Markup Language (XML) documents. Thus, the paper(More)
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Information available nowadays in web repositories is big and potentially rich. Natural Language Processing (NLP) systems can play a key role in revealing information: they can analyze and extract relevant information from web content, transforming it into machine-processable annotation data for building knowledge [Campos et al. 2014]. Most state-of-the-art(More)