Proceedings of the 4th International Conference on New Computational Social Science (ICNCSS 2024)

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Research on Hidden Parenthood Relationship of Figures in Long-text Kung Fu Novels

Authors
Jinshan Qi1, Bin Gui1, Xun Liang2, *, Junheng Gao2
1School of Computer Science and Technology, Huai’an Key Laboratory of Big Data Intelligent Computing and Analysis, Huaiyin Normal University, Huai’an, Jiangsu, China
2School of Information, Renmin University of China, Beijing, China
*Corresponding author. Email: xun__liang@163.com
Corresponding Author
Xun Liang
Available Online 29 April 2024.
DOI
10.2991/978-2-38476-230-9_7How to use a DOI?
Keywords
dependency parsing analysis; person relationship extraction; fixed-sentence rules; parent-child relationship
Abstract

This paper proposes a method based on the dependency syntax tree microstructure analysis, and extracts the parenthood relationship of novel characters from the long text Kung Fu novels by means of fixed-sentence rules, pronoun digestion and dictionary. The dependency syntax tree microstructure defines the concept of micro-structure pattern. The fixed-sentence rules are based on the syntactic habits in daily life, and combine the methods of pronoun digestion and dictionary to filter and combine the dependency syntax tree microstructure model to extract the relationship of characters and get the parenthood candidate set (PCS). In the PCS, the intimate relationship field of different granularity is obtained by calculating the intimacy relation matrix, and the hidden parenthood information (HPI) item of the candidate name is calculated in the intimate relationship field to obtain the hidden parenthood relationship score matrix. Thus, hidden parenthood relationships can be found from the PCS. The intimate relationship field of different granularity focuses on the relationships between characters, while the HPI is used to calculate the relationship between characters and keywords. Experiments prove that the method is feasible and effective.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 4th International Conference on New Computational Social Science (ICNCSS 2024)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
29 April 2024
ISBN
10.2991/978-2-38476-230-9_7
ISSN
2352-5398
DOI
10.2991/978-2-38476-230-9_7How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Jinshan Qi
AU  - Bin Gui
AU  - Xun Liang
AU  - Junheng Gao
PY  - 2024
DA  - 2024/04/29
TI  - Research on Hidden Parenthood Relationship of Figures in Long-text Kung Fu Novels
BT  - Proceedings of the 4th International Conference on New Computational Social Science (ICNCSS 2024)
PB  - Atlantis Press
SP  - 48
EP  - 65
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-230-9_7
DO  - 10.2991/978-2-38476-230-9_7
ID  - Qi2024
ER  -