NLP and Large-Scale Information Retrieval on Mathematical Texts

  • Yihe DongEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10931)


We present a recommender system covering math and math physics papers from the arXiv, to assist researchers to quickly retrieve theorems and discover similar results from this vast corpus. The retrieval aims to discover not just syntactic, but also semantic similarity. We will discuss the challenges encountered and the experimental methodologies used.


NLP Information retrieval 



We would like to thank Jeremy Michelson and Michael Trott for continuously lending their ears and ideas throughout this project, as well as Rob Y. Lewis and the ICMS reviewer for helpful comments on an earlier draft of this paper.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Wolfram ResearchChampaignUSA

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