The KnowledgeStore: A Storage Framework for Interlinking Unstructured and Structured Knowledge
نویسندگان
چکیده
Although the quantity of structured information on the Web and within organizations is increasing, the majority of information remains available only in unstructured form. While different in form, both unstructured and structured information sources provide information about entities in the world and their properties and relations; still, frameworks for their seamless integration have not been deeply investigated. In this paper the authors describe the KnowledgeStore, a scalable, fault-tolerant, and Semantic Web grounded open-source storage system for interlinking structured and unstructured data. They present the concept, design, function and implementation of the system, and report on its concrete usage in three application scenarios within the NewsReader EU project, where it stores and supports the querying of millions of news articles interlinked with millions of RDF triples extracted from text and imported from Linked Open Data sources. The authors report on data population and data retrieval performances of the system measured through a number of experiments, and they also discuss the practical issues and lessons learned from these experiences. The KnowledgeStore: A Storage Framework for Interlinking Unstructured and Structured Knowledge
منابع مشابه
Integrating NLP and SW with the KnowledgeStore
We showcase the KnowledgeStore (KS), a scalable, fault-tolerant, and Semantic Web grounded storage system for interlinking unstructured and structured contents. The KS contributes to bridge the unstructured (e.g., textual document, web pages) and structured (e.g., RDF, LOD) worlds, enabling to jointly store, manage, retrieve, and query, both typologies of contents.
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We showcase the KnowledgeStore, a scalable, fault-tolerant, and Semantic Web grounded framework for interlinking unstructured (e.g., textual documents, web pages) and structured (e.g., RDF, LOD) contents, enabling to jointly store, manage, retrieve, and query, both typologies of contents.
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عنوان ژورنال:
- Int. J. Semantic Web Inf. Syst.
دوره 11 شماره
صفحات -
تاریخ انتشار 2015