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Managing Large Volumes of Interlinked Text and Knowledge With the KnowledgeStore
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Author(s): Francesco Corcoglioniti (Fondazione Bruno Kessler, Italy), Marco Rospocher (Fondazione Bruno Kessler, Italy), Roldano Cattoni (Fondazione Bruno Kessler, Italy), Bernardo Magnini (Fondazione Bruno Kessler, Italy)and Luciano Serafini (Fondazione Bruno Kessler, Italy)
Copyright: 2018
Pages: 30
Source title:
Innovations, Developments, and Applications of Semantic Web and Information Systems
Source Author(s)/Editor(s): Miltiadis D. Lytras (American College of Greece, Greece), Naif Aljohani (King Abdulaziz University, Saudi Arabia), Ernesto Damiani (University of Milan, Italy)and Kwok Tai Chui (The Open University of Hong Kong, Hong Kong)
DOI: 10.4018/978-1-5225-5042-6.ch002
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Abstract
This chapter describes the KnowledgeStore, a scalable, fault-tolerant, and Semantic Web grounded open-source storage system to jointly store, manage, retrieve, and query interlinked structured and unstructured data, especially designed to manage all the data involved in Knowledge Extraction applications. The chapter presents the concept, design, function and implementation of the KnowledgeStore, and reports on its concrete usage in four application scenarios within the NewsReader EU project, where it has been successfully used to store and support the querying of millions of news articles interlinked with billions of RDF triples, both extracted from text and imported from Linked Open Data sources.
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