Towards Automatic Mathematical Exercise Solving

Tianyu Zhao*, Chengliang Chai, Yuyu Luo, Jianhua Feng, Yan Huang, Songfan Yang, Haitao Yuan, Haoda Li, Kaiyu Li, Fu Zhu, Kang Pan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

Knowledge graphs are widely applied in many applications. Automatically solving mathematical exercises is also an interesting task which can be enhanced by knowledge reasoning. In this paper, we design MathGraph, a knowledge graph aiming to solve high school mathematical exercises. Since it requires fine-grained mathematical derivation and calculation of different mathematical objects, we design a crowdsourcing-based method to help build MathGraph. MathGraph supports massive kinds of mathematical objects, operations and constraints which may be involved in exercises. Furthermore, we propose an algorithm to align a semantically parsed exercise to MathGraph and figure out the answer automatically. Extensive experiments on real-world datasets verify the effectiveness of MathGraph.

Original languageEnglish
Pages (from-to)179-192
Number of pages14
JournalData Science and Engineering
Volume4
Issue number3
DOIs
Publication statusPublished - 1 Sept 2019
Externally publishedYes

Keywords

  • Crowdsourcing
  • Knowledge graph
  • Knowledge reasoning
  • Mathematical exercise

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