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2019 | OriginalPaper | Buchkapitel

MathGraph: A Knowledge Graph for Automatically Solving Mathematical Exercises

verfasst von : Tianyu Zhao, Yan Huang, Songfan Yang, Yuyu Luo, Jianhua Feng, Yong Wang, Haitao Yuan, Kang Pan, Kaiyu Li, Haoda Li, Fu Zhu

Erschienen in: Database Systems for Advanced Applications

Verlag: Springer International Publishing

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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, the design of MathGraph has major differences from existing knowledge graphs. 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.

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Vorheriges Kapitel Leon: A Distributed RDF Engine for Multi-query Processing

Nächstes Kapitel Multi-hop Path Queries over Knowledge Graphs with Neural Memory Networks

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Titel: MathGraph: A Knowledge Graph for Automatically Solving Mathematical Exercises
verfasst von: Tianyu Zhao
Yan Huang
Songfan Yang
Yuyu Luo
Jianhua Feng
Yong Wang
Haitao Yuan
Kang Pan
Kaiyu Li
Haoda Li
Fu Zhu
Verlag: Springer International Publishing
Buch: Database Systems for Advanced Applications
Print ISBN: 978-3-030-18575-6

Electronic ISBN: 978-3-030-18576-3

Copyright-Jahr: 2019
DOI: https://doi.org/10.1007/978-3-030-18576-3_45

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