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Knowledge Extraction System from Unstructured Documents

dc.contributor.authorRodriguez T.
dc.contributor.authorAguilar J.
dc.date.accessioned2020-09-02T22:27:04Z
dc.date.available2020-09-02T22:27:04Z
dc.date.issued2018
dc.identifier10.1109/TLA.2018.8327424
dc.identifier.citation16, 2, 639-646
dc.identifier.issn15480992
dc.identifier.urihttps://hdl.handle.net/20.500.12728/6040
dc.descriptionIn this paper, we design and implement a knowledge extraction system from unstructured documents (unstructured documents are documents where the information is in natural language, and require natural language processing techniques for processing) in HTML format. Basically, the system allows to transform the content of a text that is in natural language, into structured and organized knowledge, semantically described (a Semantic Ontology). Therefore, it is proposed to generate semantic knowledge based on the extraction of entities and relationships, where entities are anything about which something can be said, and relations the interactions between entities. From the generated semantic knowledge model, it is possible to infer new knowledge, such as lexicons, taxonomies and specialized terminological bases. The system can be used by any semantic processing application, in its processes of enriching its information and knowledge. © 2003-2012 IEEE.
dc.language.isoes
dc.publisherIEEE Computer Society
dc.subjectKnowledge Extraction
dc.subjectNatural Language Processing
dc.subjectSemantic Knowledge
dc.subjectSemantic Ontologies
dc.subjectExtraction
dc.subjectKnowledge based systems
dc.subjectOntology
dc.subjectSemantics
dc.subjectDesign and implements
dc.subjectKnowledge extraction
dc.subjectNatural languages
dc.subjectSemantic knowledge
dc.subjectSemantic ontology
dc.subjectSemantic processing
dc.subjectUnstructured documents
dc.subjectNatural language processing systems
dc.titleKnowledge Extraction System from Unstructured Documents
dc.typeArticle


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