Information extraction from mathematical texts by means of natural language processing techniques

  • Authors:

  • Sabina Jeschke;Marc Wilke;Marie Blanke;Nicole M. Natho;Olivier F. Pfeiffer

  • Affiliations:

  • University of Stuttgart;University of Stuttgart;Berlin University of Technology;Berlin University of Technology;Berlin University of Technology

  • Venue:
  • Proceedings of the international workshop on Educational multimedia and multimedia education
  • Year:
  • 2007

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Abstract

Particularly with regard to the widespread use of the internet, the increasing amount of scientific publications creates new requirements for sophisticated information retrieval systems. The discovery of semantic annotation for describing mathematical texts themselves and the structure of the observed mathematical field is an important issue supporting such information retrieval systems. A lot of good statistical approaches for finding correlations in texts exist e.g. as used by Google. mArachna follows a different approach and uses natural language processing techniques to recover all the fine-grained information snippets within mathematical texts. The extracted information is stored in knowledge bases, creating a low-level ontology of mathematics. In this article we represent our further developments in this field and the technical implementation of the mArachna prototype.