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Formula Citation Graph Based Mathematical Information Retrieval

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Document Analysis and Recognition – ICDAR 2021 (ICDAR 2021)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12821))

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Abstract

Nowadays, with the quick availability and growth of formulae on the Web, the question of how to effectively retrieve the relevant documents about formulae, namely formula retrieval, has attracted much attention from the researchers of mathematical information retrieval (MIR). Existing MIR search engines have explored much information of formulae such as characters, layout structure, the formula context. However, little attention has been paid to the link or citation relations of formulae among different documents, while these relations are helpful for searching some related formulae whose appearances are not similar to the query formula. Therefore, in this paper, we design a Formula Citation Graph (FCG) to ‘dig out’ the link or citation relations between formulae. FCG has two main advantages: 1) The graph could generate the descriptive keywords of formulae to enrich the semantics of formula queries. 2) The graph is employed to balance the ranking results between the text and structure matching. The experimental results demonstrate that the link or citation relations among formulae are helpful for MIR.

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Notes

  1. 1.

    http://ntcir-math.nii.ac.jp/.

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Acknowledgements

This work is supported by the projects of National Natural Science Foundation of China (No. 61876003), National Key R&D Program of China (2019YFB1406303), Guangdong Basic and Applied Basic Research Foundation (2019A1515010837) and the Fundamental Research Funds for the Central Universities, which is also a research achievement of Key Laboratory of Science, Technology and Standard in Press Industry (Key Laboratory of Intelligent Press Media Technology).

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Authors and Affiliations

  1. Wangxuan Institute of Computer Technology, Peking University, Beijing, China

    Ke Yuan, Liangcai Gao & Zhi Tang

  2. School of Public Affairs, Zhejiang University, Hangzhou, China

    Zhuoren Jiang

Authors
  1. Ke Yuan
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  2. Liangcai Gao
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  3. Zhuoren Jiang
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  4. Zhi Tang
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Corresponding author

Correspondence to Liangcai Gao .

Editor information

Editors and Affiliations

  1. Universitat Autònoma de Barcelona, Barcelona, Spain

    Josep Lladós

  2. Lehigh University, Bethlehem, PA, USA

    Daniel Lopresti

  3. Kyushu University, Fukuoka-shi, Japan

    Seiichi Uchida

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Yuan, K., Gao, L., Jiang, Z., Tang, Z. (2021). Formula Citation Graph Based Mathematical Information Retrieval. In: Lladós, J., Lopresti, D., Uchida, S. (eds) Document Analysis and Recognition – ICDAR 2021. ICDAR 2021. Lecture Notes in Computer Science(), vol 12821. Springer, Cham. https://doi.org/10.1007/978-3-030-86549-8_40

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  • DOI: https://doi.org/10.1007/978-3-030-86549-8_40

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  • Print ISBN: 978-3-030-86548-1

  • Online ISBN: 978-3-030-86549-8

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