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A Survey of CRF Algorithm Based Knowledge Extraction of Elementary Mathematics in Chinese

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Abstract

Chinese word segmentation is an important research direction in related research on elementary mathematics knowledge extraction. The speed of segmentation directly affects subsequent applications, and the accuracy of segmentation directly affects corresponding research in the next step. In the machine learning methods for extracting basic mathematical knowledge points, the Conditional Random Field (CRF) model implements new word discovery well, and is increasingly used in knowledge extraction of basic mathematics. This article first introduces the traditional CRF process of named entity recognition. Then, an improved algorithm CRF++for conditional field model is proposed. Since the recognition rate of named entities based on traditional machine learning methods is not high, a post-processing method for entity recognition that automatically generates a dictionary is proposed. After identifying mathematical entities, a pruning strategy combining Viterbi algorithm and rules is proposed to achieve a higher recognition rate of elementary mathematical entities. Finally, several methods of disambiguation after entity recognition are introduced.

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Acknowledgements

This work was supported by the Natural Science Foundation of Hunan Province with No.2020JJ4434; Key Scientific Research Projects of Department of Education of Hunan Province with No.19A312; Hunan Provincial Science & Technology Project with No.2018TP1018 and No.2018RS3065; National Natural Science Foundation of China with No.61502254; Open Project Program of the State Key Lab of CAD&CG with No.A1926 of Zhejiang University.

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Authors and Affiliations

  1. Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing, Hunan Normal University, Changsha, 410081, China

    Shuai Liu, Tenghui He & Jianhua Dai

  2. College of Information Science and Engineering, Hunan Normal University, Changsha, 410081, China

    Shuai Liu, Tenghui He & Jianhua Dai

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  1. Shuai Liu
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  2. Tenghui He
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  3. Jianhua Dai
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Correspondence to Shuai Liu.

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Liu, S., He, T. & Dai, J. A Survey of CRF Algorithm Based Knowledge Extraction of Elementary Mathematics in Chinese. Mobile Netw Appl 26, 1891–1903 (2021). https://doi.org/10.1007/s11036-020-01725-x

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