PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Kobos M., Bolikowski ┼., Horst M., Manghi P., Manola N., Schirrwagen J. Information inference in scholarly communication infrastructures: the OpenAIREplus project experience. In: Procedia Computer Science, vol. 38 pp. 92 - 99. Special issue: 10th Italian Research Conference on Digital Libraries, IRCDL 2014. Maristella Agosti, Tiziana Catarci, Floriana Esposito (eds.). Elsevier, 2014.
 
 
Abstract
(English)
The Information Inference Framework presented in this paper provides a general-purpose suite of tools enabling the definition and execution of flexible and reliable data processing workflows whose nodes offer application-specific processing capabilities. The IIF is designed for the purpose of processing big data, and it is implemented on top of Apache Hadoop-related technologies to cope with scalability and high-performance execution requirements. As a proof of concept we will describe how the framework is used to support linking and contextualization services in the context of the OpenAIRE infrastructure for scholarly communication
URL: http://www.sciencedirect.com/science/article/pii/S1877050914013763
DOI: 10.1016/j.procs.2014.10.016
Subject OpenAIRE infrastructure
Data processing system
Data mining
Text mining
Big data
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