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International Conference on Information

iConference 2021: Diversity, Divergence, Dialogue pp 502–513Cite as

A Semantic Framework for Chinese Historical Events Based on Linked Data and Knowledge Graph

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12645))

Abstract

In the era of big data, data redundancy has become an obstacle to deep reading. The objective of linked data as a new data organization model is to transform data into structured data following unified standards. The lack of Chinese conceptual terms has seriously hindered the semantization and standardization of Chinese domain ontology. Taking Chinese historical events as an example, ontology technology is used in this paper to standardize the definition of concepts and semantic relations in domain knowledge. Moreover, concepts from text resources are extracted through a deep learning algorithm Bi-LSTM-CRFs and combined with an external knowledge base to realize the fusion of related data within various data sets. Ultimately, the knowledge ontology of historical events is displayed in the way of a knowledge graph to further explore the practical application. The results show that the accuracy of the terms extraction of historical events is about 80% indicating the good recognition performance and portability of the model.

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Acknowledgement

This work is an outcome of project “Research on Semantic Parsing and Humanities Computing of Chinese Intangible Cultural Heritage Text Driven by Linked Data” (No. 72074108) supported by National Natural Science Foundation of China and “The Semantic Analysis and Knowledge Graph Research of Local Chronicle Text Oriented to Humanistic Computing” (No. 14370113) supported by the Fundamental Research Funds for the Central Universities.

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Authors and Affiliations

  1. School of Information Management, Nanjing University, Nanjing, 210023, China

    Hao Wang, Yueyan Li & Sanhong Deng

  2. Jiangsu Key Laboratory of Data Engineering and Knowledge Service, Nanjing, 210023, China

    Hao Wang, Yueyan Li & Sanhong Deng

Authors
  1. Hao Wang
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  2. Yueyan Li
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  3. Sanhong Deng
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Corresponding author

Correspondence to Yueyan Li .

Editor information

Editors and Affiliations

  1. Humboldt University of Berlin, Berlin, Germany

    Katharina Toeppe

  2. Renmin University of China, Beijing, China

    Hui Yan

  3. The University of Hong Kong, Hong Kong, Hong Kong

    Samuel Kai Wah Chu

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Wang, H., Li, Y., Deng, S. (2021). A Semantic Framework for Chinese Historical Events Based on Linked Data and Knowledge Graph. In: Toeppe, K., Yan, H., Chu, S.K.W. (eds) Diversity, Divergence, Dialogue. iConference 2021. Lecture Notes in Computer Science(), vol 12645. Springer, Cham. https://doi.org/10.1007/978-3-030-71292-1_39

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  • DOI: https://doi.org/10.1007/978-3-030-71292-1_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-71291-4

  • Online ISBN: 978-3-030-71292-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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