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Ontology-Driven Information Extraction from Research Publications

  • Vayianos Pertsas
  • Panos Constantopoulos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11057)

Abstract

Extraction of information from a research article, association with other sources and inference of new knowledge is a challenging task that has not yet been entirely addressed. We present Research Spotlight, a system that leverages existing information from DBpedia, retrieves articles from repositories, extracts and interrelates various kinds of named and non-named entities by exploiting article metadata, the structure of text as well as syntactic, lexical and semantic constraints, and populates a knowledge base in the form of RDF triples. An ontology designed to represent scholarly practices is driving the whole process. The system is evaluated through two experiments that measure the overall accuracy in terms of token- and entity- based precision, recall and F1 scores, as well as entity boundary detection, with promising results.

Keywords

Information extraction from text Ontology population Linked data Knowledge base creation 

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Department of InformaticsAthens University of Economics and BusinessAthensGreece
  2. 2.Digital Curation UnitAthena Research CentreAthensGreece

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