Natural Language Processing Methods for Extracting Information from Mathematical Texts

  • Nicole Natho
  • Sabina Jeschke
  • Olivier Pfeiffer
  • Marc Wilke
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 4)

Managing knowledge takes up a significant role in modern organization and society. Every day, numerous books and publications are released to disseminate new knowledge. In particular, the World Wide Web is an example of a huge unsystematic knowledge base that provides access to a lot of information. Too much information leads to the proliferation of knowledge called “information glut,” which is not easy to handle. Applications to specialize and generalize information gain in importance in the search for solutions to face the new challenges.


Knowledge Base Mathematical Knowledge Extract Information Semantic Annotation Mathematical Language 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Hilbert D (1928) Die grundlagen der mathematik. Abhandlungen aus dem Mathematischen Seminar der Hamburgischen Universität 6:65–85zbMATHCrossRefGoogle Scholar
  2. 2.
    Bourbaki N (1974) Die Architektur der Mathematik. Mathematiker über die Mathematik. Springer, BerlinGoogle Scholar
  3. 3.
    Gödel K (1931–1932) Über formal unentscheidbare Sätze der Principia Mathematica und verwandte Systeme I. Monatsheft f. Mathematik und Physik 147fGoogle Scholar
  4. 4.
    The Apache Software Foundation: Apache Lucene.
  5. 5.
    Jeschke S (2004) Mathematik in Virtuellen Wissensräumen—IuK-Strukturen und IT-Technologien in Lehre und Forschung. PhD thesis, Technische Universität BerlinGoogle Scholar
  6. 6.
    Natho N (2005) mArachna: Eine Semantische Analyse der Mathematischen Sprache für ein Computergestütztes Information Retrieval. PhD thesis, Technische Universität BerlinGoogle Scholar
  7. 7.
    Grottke S, Jeschke S, Natho N, Seiler R (2005) mArachna: A classification scheme for semantic retrieval in elearning environments in mathematics. In: Proc. of the 3rd International Conference on Multimedia and ICTs in Education, June 7–10, 2005, Caceres/SpainGoogle Scholar
  8. 8.
    W3C: Web Ontology Language.
  9. 9.
    The TEI Consortium: Text Encoding Initiative.
  10. 10.
  11. 11.
  12. 12.
    Müller S (2005) Deutsche syntax deklarativ: Head-driven phrase structure grammar für das Deutsche. In: Linguistische Arbeiten 394. Max Niemeyer Verlag, TübingenGoogle Scholar
  13. 13.
    Mozilla Foundation: Rhino.
  14. 14.
    Jena: A Semantic Web Framework for Java.
  15. 15.
  16. 16.
    Wüst R (2005) Mathematik für Physiker und Mathematiker, Bd.1. Wiley-VCHGoogle Scholar
  17. 17.
    Gruber T, Olsen G (1994) An Ontology for Engineering Mathematics. Technical Report KSL-94-18, Stanford UniversityGoogle Scholar
  18. 18.
    Baur J (1999) Syntax und Semantik Mathematischer Texte. Master’s thesis, Universität des Saarlandes, Fachbereich ComputerlinguistikGoogle Scholar
  19. 19.
    Wolfram Research: MathWorld.
  20. 20.
    Fellbaum C (1998) WordNet: An Electronic Lexical Database. MIT Press, Cambridge, LondonzbMATHGoogle Scholar
  21. 21.
    Fellbaum C WordNet.
  22. 22.
  23. 23.
    Helbig H (2006) Knowledge Representation and the Semantics of Natural Language. Springer, BerlinzbMATHGoogle Scholar
  24. 24.
    Urban J (2006) MoMM—Fast interreduction and retrieval in large libraries of formalized mathematics. International Journal on Artificial Intelligence Tools 15(1):109–130CrossRefGoogle Scholar
  25. 25.
    Urban J (2005) MizarMode—An integrated proof assistance tool for the mizar way of formalizing mathematics. Journal of Applied Logic doi:10.1016/j.jal.2005.10.004Google Scholar
  26. 26.
    Urban J (2002) XML-izing Mizar: Making Semantic Processing and Presentation of MML Easy, MKM2005Google Scholar
  27. 27.
    Pinkall M, Siekmann J, Benzmüller C, Kruijff-Korbayova I. DIALOG.
  28. 28.
    Asperti A, Padovani L, Sacerdoti Coen C and Schena I (2001) HELM and the semantic web. In: Boulton RJ, Jackson PB, eds. Theorem Proving in Higher Order Logics, 14th International Conference, TPHOLs 2001, Edinburgh, Scotland, UK, September 3–6, 2001, Proceedings. Volume 2152 of Lecture Notes in Computer Science, SpringerGoogle Scholar
  29. 29.
    Asperti A, Zacchiroli S (2004) Searching mathematics on theWeb: State of the art and future developments. In: Joint Proceedings of the ECM4 Satellite Conference on Electronic Publishing at KTH Stockholm, AMS–SM M Special Session, HoustonGoogle Scholar
  30. 30.
    Albayrak S, Wollny S, Varone N, Lommatzsch A, Milosevic D (2005) Agent technology for personalized information filtering: the PIA-system. ACM Symposium on Applied ComputingGoogle Scholar
  31. 31.
    Collier N, K T. May (2002) PIA-core: Semantic annotation through example-based learning. Third International Conference on Language Resources and Evaluation, pp 1611–1614Google Scholar
  32. 32.
    The PIA Project: PIA.

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Nicole Natho
    • 1
  • Sabina Jeschke
    • 2
  • Olivier Pfeiffer
    • 1
  • Marc Wilke
    • 2
  1. 1.MuLF—Center for Multimedia in Education and ResearchBerlin University of TechnologyGermany
  2. 2.RUS—Center of Information TechnologiesUniversity of StuttgartGermany

Personalised recommendations