Skip to main content

Entity Linking for Mathematical Expressions in Scientific Documents

  • Conference paper
  • First Online:
Digital Libraries: Knowledge, Information, and Data in an Open Access Society (ICADL 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10075))

Included in the following conference series:

Abstract

This paper addresses the challenge of determining the identity of math expressions in scientific documents by linking these expressions to their corresponding Wikipedia articles. Math expressions are frequently used to denote important concepts in scientific documents, yet several of them, for example, famous equations, often have minimal explanation in the documents. This task will allow us to obtain an additional explanation from Wikipedia regarding these math expressions. This paper proposes an approach to this challenge, where the structures and surrounding text of math expressions are used for math entity linking. Our initial evaluation shows that a balanced combination of math structures and textual descriptions is required to obtain reliable linking performance.

This work was supported by JSPS Kakenhi Grant Number 14J09896, and CREST, JST.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    http://www.swi-prolog.org/.

  2. 2.

    https://aclweb.org/anthology.

  3. 3.

    http://www.inftyreader.org.

  4. 4.

    http://dlmf.nist.gov/LaTeXML/.

References

  1. Agrawal, R., Gollapudi, S., Kannan, A., Kenthapadi, K.: Data mining for improving textbooks. SIGKDD Explor. Newsl. 13(2), 7–19 (2012)

    Article  Google Scholar 

  2. Cheng, X., Roth, D.: Relational Inference for Wikification. In: Proceedings of EMNLP (2013)

    Google Scholar 

  3. Cucerzan, S.: Large-scale named entity disambiguation based on wikipedia data. In: Proceedings of the Joint Conference of EMNLP-CoNLL (2007)

    Google Scholar 

  4. Kristianto, G.Y., Topić, G., Aizawa, A.: The MCAT math retrieval system for NTCIR-12 MathIR task. In: Proceedings of the 12th NTCIR Conference (2016)

    Google Scholar 

  5. Mihalcea, R., Csomai, A., Wikify!: Linking documents to encyclopedic knowledge. In: Proceedings of the 16th ACM CIKM (2007)

    Google Scholar 

  6. Milne, D., Witten, I.H.: Learning to link with wikipedia. In: Proceedings of the 17th ACM CIKM (2008)

    Google Scholar 

  7. Ni, Y., Xu, Q.K., Cao, F., Mass, Y., Sheinwald, D., Zhu, H.J., Cao, S.S.: Semantic documents relatedness using concept graph representation. In: Proceedings of the 9th ACM WSDM (2016)

    Google Scholar 

  8. Pagel, R., Schubotz, M.: Mathematical language processing project. In: Work in Progress Track at CICM (2014)

    Google Scholar 

  9. Rose, S., Engel, D., Cramer, N., Cowley, W.: Automatic Keyword Extraction from Individual Documents. Applications and Theory, In Text Mining (2010)

    Google Scholar 

  10. Zanibbi, R., Aizawa, A., Kohlhase, M., Ounis, I., Topić, G., Davila, K.: NTCIR-12 MathIR task overview. In: NTCIR, National Institute of Informatics (NII) (2016)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Giovanni Yoko Kristianto .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing AG

About this paper

Cite this paper

Kristianto, G.Y., Topić, G., Aizawa, A. (2016). Entity Linking for Mathematical Expressions in Scientific Documents. In: Morishima, A., Rauber, A., Liew, C. (eds) Digital Libraries: Knowledge, Information, and Data in an Open Access Society. ICADL 2016. Lecture Notes in Computer Science(), vol 10075. Springer, Cham. https://doi.org/10.1007/978-3-319-49304-6_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-49304-6_18

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49303-9

  • Online ISBN: 978-3-319-49304-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics