Semantic Web Evaluation Challenge

SemWebEval 2014: Semantic Web Evaluation Challenge pp 120-126

Extraction and Characterization of Citations in Scientific Papers

Conference paper

DOI: 10.1007/978-3-319-12024-9_16

Volume 475 of the book series Communications in Computer and Information Science (CCIS)
Cite this paper as:
Bertin M., Atanassova I. (2014) Extraction and Characterization of Citations in Scientific Papers. In: Presutti V. et al. (eds) Semantic Web Evaluation Challenge. SemWebEval 2014. Communications in Computer and Information Science, vol 475. Springer, Cham

Abstract

We propose a hybrid method for the extraction and characterization of citations in scientific papers using machine learning combined with rule-based approaches. Our protocol consists of the extraction of metadata, bibliography parsing, section titles processing, and find-grained semantic annotation on the sentence level of texts. This allows us to generate Linked Open Data from a set of research papers in XML.

Keywords

Semantic annotationCitation actsCRFRDF graphsLinked Open DataBibliography parsing

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.CIRSTUniversité du Québec à MontréalMontrealCanada