research-article

Perspective of Digital Humanities On Person Names in Chinese Pre-Qin Classic

Authors:

Shuiqing HuangAuthors Info & Claims

ACM Journal on Computing and Cultural Heritage, Volume 17, Issue 2

Article No.: 32, Pages 1 - 19

https://doi.org/10.1145/3647997

Published: 17 April 2024 Publication History

Abstract

Knowledge annotation and mining from ancient Chinese classics have become a new trend in digital humanities research in China, and historical persons get the most attention. However, few studies have focused exclusively on person names, which is rather important for understanding Chinese traditional culture. This study focused on person names in Chinese Pre-Qin classics. We conducted a humanities computing study on pre-Qin person name knowledge through an in-depth categorization and manual annotation of person name components. The results included the disambiguation of person names, a statistical distribution of famous persons, patterns in name components, and statistical analysis of name components. Furthermore, machine learning methods on the named entity recognition of person name knowledge were also examined, indicating the feasibility of future related research.

References

[1]

A. Barforoush, H. Shirazi, and H. Emami. 2017. A new classification framework to evaluate the entity proiling on the Web: Past, present and future. ACM Computing Surveys 50, 3 (2017), 39:1–39:39.

Digital Library

[2]

Bolin Chang, Chen Wan, Bin Li, Xinyu Chen, Minxuan Feng, and Dongbo Wang. 2021. The construction and application for digital humanities knowledge base of ancient books based on word and entity annotation: A case study on zhou qin han annals of zizhitongjian. Library and Information Service 65, 22 (2021), 134--142.

[3]

C.-M. Chen and C. Chang. 2019. A Chinese ancient book digital humanities research platform to support digital humanities research. The Electronic Library 37, 2 (2019), 314–336.

[4]

J. Chen and L. H. Tsui. 2022. Debating and developing digital humanities in China. In New or Old? D. Fiormonte, S. Chaudhuri, and P. Ricaurte (Eds.), Debates in the Digital Humanities. University of Minnesota Press, Minneapolis, 71–86.

[5]

Tao Chen, Wei Liu, Rongrong Shan, and Qinghua Zhu. 2019. Research on the application of knowledge graph in digital humanities. Journal of Library Science in China 45, 6 (2019), 34--49.

[6]

Sanhong Deng, Haotian Hu, Hao Wang, and Dongbo Wang. 2021. Review of automatic processing of ancient chinese character and prospects for its development trends in new era. Scientific Information Research 3, 1 (2021), 1--20.

[7]

Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. BERT: Pre-training of deep bidirectional transformers for language understanding. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), June 2019, Minneapolis, Minnesota. Association for Computational Linguistics, Minneapolis, Minnesota, 4171--4186.

[8]

Yue Du, Dongbo Wang, Chuan Jiang, Runhua Xu, Bin Li, Chao Xu, and Chenfei Xu. 2021. Construction and application of entity recognition model based on deep learning of classics in digital humanities. Library and Information Service 65, 3 (2021), 100--108.

[9]

H. Emami. 2019. A graph-based approach to person name disambiguation in Web. ACM Transactions on Management Information Systems 10, 2 (2019), 4:1–4:25.

Digital Library

[10]

H. Emami, H. Shirazi, and A. Abdollahzadeh Barforoush. 2017. A semantic approach to cross-document person profiling in Web. AI Communications 30, 6 (2017), 363–391.

Digital Library

[11]

H. Emami, H. Shirazi, and A. A. Barforoush. 2018. Web person name disambiguation using social links and enriched profile information. Computing and Informatics 37 (2018), 1485–1515.

[12]

S. Huang and D. Wang. 2017. Review and trend of researches on ancient Chinese character information processing. Library and Information Service 61, 12 (2017), 43–49.

[13]

S. Huang, D. Wang, and L. He. 2015. Exploring of word segmentation for fore-Qin literature based on the domain glossary of sinological index series. Library and Information Service 59, 11 (2015), 127–133.

[14]

X. Li. 1987. Archaeological discoveries and the ancient family name system. Archaeology 3 (1987), 253 -257 +241. 488

[15]

X. Li. 1991. Several questions about pre-Qin people's names. Historical Research 05 (1991), 106–111.

[16]

Zhangchao Li, Zhongkai Li, and L. He. 2020. Study on the extraction method of war events in Zuo Zhuan. Library and Information Service 64, 07 (2020), 20–29.

[17]

C.-L. Liu, T. J. Mazanec, and J. R. Tharsen. 2018. Exploring Chinese poetry with digital assistance: Examples from linguistic, literary, and historical viewpoints. Journal of Chinese Literature and Culture 5, 2 (2018), 276–321.

[18]

Z. Liu, J. Dang, and Z. Zhang. 2020. Research on automatic extraction of historical events and construction of event graph based on historical records. Library and Information Service 64, 11 (2020), 116–124.

[19]

Shuang Liu, Hui Yang, Jiayi Li, and Simon Kolmanič. 2021. Chinese Named Entity Recognition Method in History and Culture Field Based on BERT. International Journal of Computational Intelligence Systems 14, 1 (September 2021), 163.

[20]

J. Liu et al. 2022. Research on SikuBERT-enhanced entity recognition of historical records from the perspective of digital humanities. Library Tribune 42, 10 (2022), 61–72.

[21]

J. Ouyang. 2016. Visual analysis and exploration of ancient texts for digital humanities research. Journal of Library Science in China 42, 02 (2016), 66–80.

[22]

H. Tian et al. 2021. AnchiBERT: A pre-trained model for ancient Chinese language understanding and generation. In Proceedings of the 2021 International Joint Conference on Neural Networks (IJCNN). 1–8.

[23]

L. H. Tsui and H. Wang. 2020. Harvesting big biographical data for Chinese history: The China biographical database (CBDB). Journal of Chinese History 中國歷史學刊 4, 2 (2020), 505–511.

[24]

R. Wang. 2003. Images of Women in Chinese Thought and Culture: Writings from the Pre-Qin Period Through the Song Dynasty. Hackett Publishing Company. https://books.google.com.tw/books?id=xQiJWZNQZfgC

[25]

X. Wang and B. Li. 2017. Automatically segmenting middle ancient Chinese words with CRFs. Data Analysis and Knowledge Discovery 1, 05 (2017), 62–70.

[26]

D. Wang, S. Huang, and L. He. 2017. Researches of automatic part-of-speech tagging for pre-Qin literature based on multi-feature knowledge. Library and Information Service 61, 12 (2017), 64–70.

[27]

D. Wang et al. 2022. Construction and application of pre-training model of “Siku Quanshu” oriented to digital humanities. Library Tribune 42, 6 (2022), 31–43.

[28]

J. Wei and R. Liu. 2019. An approach of constructing knowledge graph of the hundred schools of thought in ancient China. In Proceedings of the 2019 ACM/IEEE Joint Conference on Digital Libraries (JCDL). IEEE, 335–336.

Digital Library

[29]

C. Xia. 2017. The opening and application of Chinese historical geography data in digital humanities projects of libraries. Journal of Library Science in China 43, 02 (2017), 40–53.

[30]

C. Yan and J. Wang. 2018. Digital humanities perspective: A study on the visualization of political network in Song dynasty based on symbolic analysis. Journal of Library Science in China 44, 05 (2018), 87–103.

[31]

Z. Yang. 2017. Study of female images in pre-Qin and Han dynasty literature. In Proceedings of the 2017 2nd International Conference on Education, Sports, Arts and Management Engineering (ICESAME ’17). Atlantis Press, 74–77.

[32]

H. Yang and J. Wang. 2019. Visualizing knowledge graph of academic inheritance in Song dynasty. Data Analysis and Knowledge Discovery 3, 6 (2019), 109–116.

[33]

H. Zhang et al. 2021. People name recognition from ancient Chinese literature using distant supervision and deep learning. In Proceedings of the 2021 2nd International Conference on Artificial Intelligence and Information Systems (ICAIIS ’21). Association for Computing Machinery, New York, NY, USA.

Digital Library

Cited By

Cui YYao SWu JLv M(2024)Linking past insights with contemporary understanding: an ontological and knowledge graph approach to the transmission of ancient Chinese classicsHeritage Science10.1186/s40494-024-01504-x12:1Online publication date: 5-Nov-2024
https://doi.org/10.1186/s40494-024-01504-x

Index Terms

Perspective of Digital Humanities On Person Names in Chinese Pre-Qin Classic
1. Applied computing
  1. Arts and humanities
2. Information systems
  1. Information retrieval
    1. Document representation
      1. Content analysis and feature selection
    2. Retrieval tasks and goals
      1. Information extraction

Recommendations

A Context-Aware Automatic Chinese Transliterated Person Names Recognition Approach
SKG '12: Proceedings of the 2012 Eighth International Conference on Semantics, Knowledge and Grids

Chinese Transliterated Person Name (TP-Name) recognition is a special challenging task in Chinese unknown word recognition and Chinese word segmentation. Most of existing researches mainly focus on recognizing the names of Chinese person while seldom ...
Applications of collaborative annotation system in digital curation, crowdsourcing, and digital humanities

PurposeCollaboratively annotating digital texts allow users to add valued information, share ideas and create knowledge. Most importantly, annotated content can help users obtain a deeper and broader understanding of a text compared to digital content ...
Digital humanities: the continuing role of serendipity in historical research
iConference '12: Proceedings of the 2012 iConference

Ebooks are being integrated into academic library catalogs---either in addition to existing resources or as a substitute to print copies. This study examines the perceptions and opinions of historians about how Ebooks, and the digitization of cultural ...

Comments

Information & Contributors

Information

Published In

cover image Journal on Computing and Cultural Heritage

Journal on Computing and Cultural Heritage Volume 17, Issue 2

June 2024

355 pages

EISSN:1556-4711

DOI:10.1145/3613557

Editor:
Karina Rodriguez-Echavarria
University of Brighton, UK

Issue’s Table of Contents

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 April 2024

Online AM: 21 February 2024

Accepted: 24 December 2023

Revised: 07 November 2023

Received: 04 April 2023

Published in JOCCH Volume 17, Issue 2

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

National Natural Science Foundation of China
National Social Science Fund of China

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

1
Total Citations
View Citations
221
Total Downloads

Downloads (Last 12 months)221
Downloads (Last 6 weeks)45

Reflects downloads up to 07 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Cui YYao SWu JLv M(2024)Linking past insights with contemporary understanding: an ontological and knowledge graph approach to the transmission of ancient Chinese classicsHeritage Science10.1186/s40494-024-01504-x12:1Online publication date: 5-Nov-2024
https://doi.org/10.1186/s40494-024-01504-x

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Full Text

View this article in Full Text.

Media

Figures

Other

Tables

View full text|Download PDF

View Issue’s Table of Contents