<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper discusses the theory and practice of constructing knowledge graph under the guidance of Xi Jinping’s socialist thought with Chinese characteristics in the new era. The study first adopts the Transformer technique based on the BERT model for effectively extracting entity relationships. Then, the article proposes an entity alignment method based on Neural Tensor Network, which enhances the semantic and structural information utilization of entity embedding vectors through optimized NTN and joint knowledge representation learning. In addition, the study employs a knowledge graph link prediction method that combines semantics and paths to fill in missing relations, and applies probabilistic soft logic to solve the inference problem of non-deterministic knowledge. Ultimately, the effectiveness of the constructed knowledge graph is demonstrated through empirical analysis of Xi Jinping’s theoretical dataset of socialist thought with Chinese characteristics in the new era. The results show that the method is more effective in dealing with polysemous words and participle errors than traditional methods, improving the data structuring level. For example, the accuracy of entity alignment is significantly better than the baseline algorithm on different datasets, e.g., on the DBP-WE dataset, its Hits@1, Hits@10 and MRR values are higher than those of the baseline by 4.01-29.49, 1.99-31.05, and 0.036-0.289, respectively. The method of this paper is remarkably effective in improving the performance of the entity alignment task, which is helpful in understanding and applying the Xi Jinping’s thought of socialism with Chinese characteristics in the new era provides new theoretical perspectives and practical methods.</p>
</abstract>

This paper discusses the theory and practice of constructing knowledge graph under the guidance of Xi Jinping’s socialist thought with Chinese characteristics in the new era. The study first adopts the Transformer technique based on the BERT model for effectively extracting entity relationships. Then, the article proposes an entity alignment method based on Neural Tensor Network, which enhances the semantic and structural information utilization of entity embedding vectors through optimized NTN and joint knowledge representation learning. In addition, the study employs a knowledge graph link prediction method that combines semantics and paths to fill in missing relations, and applies probabilistic soft logic to solve the inference problem of non-deterministic knowledge. Ultimately, the effectiveness of the constructed knowledge graph is demonstrated through empirical analysis of Xi Jinping’s theoretical dataset of socialist thought with Chinese characteristics in the new era. The results show that the method is more effective in dealing with polysemous words and participle errors than traditional methods, improving the data structuring level. For example, the accuracy of entity alignment is significantly better than the baseline algorithm on different datasets, e.g., on the DBP-WE dataset, its Hits@1, Hits@10 and MRR values are higher than those of the baseline by 4.01-29.49, 1.99-31.05, and 0.036-0.289, respectively. The method of this paper is remarkably effective in improving the performance of the entity alignment task, which is helpful in understanding and applying the Xi Jinping’s thought of socialism with Chinese characteristics in the new era provides new theoretical perspectives and practical methods.

Theoretical Advancement of Xi Jinping’s Socialist Thought with Chinese Characteristics in the New Era under the Construction of Knowledge Map

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper discusses the theory and practice of constructing knowledge graph under the guidance of Xi Jinping’s socialist thought with Chinese characteristics...

Theoretical Advancement of Xi Jinping’s Socialist Thought with Chinese Characteristics in the New Era under the Construction of Knowledge Map

Online veröffentlicht: 26. Feb. 2024

Seitenbereich: -

Eingereicht: 15. Jan. 2024

Akzeptiert: 20. Jan. 2024

DOI: https://doi.org/10.2478/amns-2024-0608

Schlüsselwörter
BERT, Transformer, Entity Alignment, Knowledge Graph, Socialist Thought

© 2024 Lili Wang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Theoretical Advancement of Xi Jinping’s Socialist Thought with Chinese Characteristics in the New Era under the Construction of Knowledge Map

Online veröffentlicht: 26. Feb. 2024

Seitenbereich: -

Eingereicht: 15. Jan. 2024

Akzeptiert: 20. Jan. 2024

DOI: https://doi.org/10.2478/amns-2024-0608

SchlüsselwörterBERT, Transformer, Entity Alignment, Knowledge Graph, Socialist Thought

© 2024 Lili Wang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
BERT, Transformer, Entity Alignment, Knowledge Graph, Socialist Thought