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NLP-Based Detection of Mathematics Subject Classification

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

Abstract

We present a classifier for the Mathematics Subject Classification (MSC) system, combining techniques in unsupervised learning such as nearest neighbors, and supervised learning such as neural networks. We will discuss the challenges presented in the classification task, such as the large number of possible classes, many with overlapping scope; and describe the data processing and experimental methodologies employed.

Keywords

Text classification NLP Neural networks 

Notes

Acknowledgments

We would like to thank Jeremy Michelson and Michael Trott for continuously lending their ears and ideas throughout this project, and the ICMS reviewer for constructive 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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