Reference Information Extraction and Processing Using Random Conditional Fields

  • Tudor Groza University of Queensland
  • AAstrand Grimnes German Research Center for Artificial Intelligence
  • Siegfried Handschuh National University of Ireland, Galway

Abstract

Fostering both the creation and the linking of data with the scope of supporting the growth of the Linked Data Web requires us to improve the acquisition and extraction mechanisms of the underlying semantic metadata. This is particularly important for the scientific publishing domain, where currently most of the datasets are being created in an author-driven, manual manner. In addition, such datasets capture only fragments of the complete metadata, omitting usually, important elements such as the references, although they represent valuable information. In this paper we present an approach that aims at dealing with this aspect of extraction and processing of reference information. The experimental evaluation shows that, currently, our solution handles very well diverse types of reference format, thus making it usable for, or adaptable to, any area of scientific publishing.

Author Biographies

Tudor Groza, University of Queensland
Postdoctoral Research Fellow, School of Information Technology and Electrical Engineering
AAstrand Grimnes, German Research Center for Artificial Intelligence
Researcher, German Research Center for Artificial Intelligence (DFKI), GmbH, Kaiserslautern, Germany
Siegfried Handschuh, National University of Ireland, Galway
Senior Lecturer/Associate Professor, National University of Ireland, Galway, Ireland
Published
2012-06-12
How to Cite
Groza, T., Grimnes, A., & Handschuh, S. (2012). Reference Information Extraction and Processing Using Random Conditional Fields. Information Technology and Libraries, 31(2), 6-20. https://doi.org/10.6017/ital.v31i2.2163
Section
Articles