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. (C) 2014 The Authors. Published by Elsevier B.V.

Information inference in scholarly communication infrastructures: the OpenAIREplus project experience

Manghi P;
2014

Abstract

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. (C) 2014 The Authors. Published by Elsevier B.V.
2014
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
OpenAIRE infrastructure
data processing system
data mining
text mining
big data
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/229407
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