Research on the Knowledge Representation Method of Power News Text Based on Time Hyperplane
To address the problem that static knowledge graphs cannot evolve over time, which leads to the conflict between entities and relations in the process of knowledge representation, this paper combines the temporal hyperplane with the translation model in knowledge representation, and proposes a knowl...
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| Veröffentlicht in: | Journal of advanced computational intelligence and intelligent informatics Jg. 29; H. 6; S. 1369 - 1376 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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Tokyo
Fuji Technology Press Co. Ltd
20.11.2025
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| ISSN: | 1343-0130, 1883-8014 |
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| Abstract | To address the problem that static knowledge graphs cannot evolve over time, which leads to the conflict between entities and relations in the process of knowledge representation, this paper combines the temporal hyperplane with the translation model in knowledge representation, and proposes a knowledge representation method based on the temporal hyperplane for power news texts. First, multiple temporal hyperplanes are established and the temporal factor is added to the scoring function of the translation model; then, the entities and relation of the power news are projected onto the temporal hyperplanes, and the optimal knowledge representation is determined according to the loss function. Taking the power news text as an example, this algorithm well resolves the time-related conflicts in the power news text, and the comprehensive indexes are significantly improved on the time-related triplets. |
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| AbstractList | To address the problem that static knowledge graphs cannot evolve over time, which leads to the conflict between entities and relations in the process of knowledge representation, this paper combines the temporal hyperplane with the translation model in knowledge representation, and proposes a knowledge representation method based on the temporal hyperplane for power news texts. First, multiple temporal hyperplanes are established and the temporal factor is added to the scoring function of the translation model; then, the entities and relation of the power news are projected onto the temporal hyperplanes, and the optimal knowledge representation is determined according to the loss function. Taking the power news text as an example, this algorithm well resolves the time-related conflicts in the power news text, and the comprehensive indexes are significantly improved on the time-related triplets. |
| Author | Wu, Yun Liu, Zhenhong Yang, Jieming Yang, Kai Du, Yan Liu, Xinru Wang, Ziyi |
| Author_xml | – sequence: 1 givenname: Yun surname: Wu fullname: Wu, Yun organization: School of Computer Science, Northeast Electric Power University, No.169 Changchun Road, Chuanying District, Jilin, Jilin 132012, China – sequence: 2 givenname: Ziyi surname: Wang fullname: Wang, Ziyi organization: School of Computer Science, Northeast Electric Power University, No.169 Changchun Road, Chuanying District, Jilin, Jilin 132012, China – sequence: 3 givenname: Yan surname: Du fullname: Du, Yan organization: Jilin Meteorological Observation and Protection Center, Jilin Meteorological Service, No.176 Suizhong Road, Lvyuan District, Changchun City, Jilin 130000, China – sequence: 4 givenname: Jieming surname: Yang fullname: Yang, Jieming organization: School of Computer Science, Northeast Electric Power University, No.169 Changchun Road, Chuanying District, Jilin, Jilin 132012, China – sequence: 5 givenname: Xinru surname: Liu fullname: Liu, Xinru organization: Shandong University of Finance and Economics, 40 Shungeng Road, Shizhong District, Jinan, Shandong 250014, China – sequence: 6 givenname: Zhenhong surname: Liu fullname: Liu, Zhenhong organization: School of Computer Science, Northeast Electric Power University, No.169 Changchun Road, Chuanying District, Jilin, Jilin 132012, China – sequence: 7 givenname: Kai surname: Yang fullname: Yang, Kai organization: School of Computer Science, Northeast Electric Power University, No.169 Changchun Road, Chuanying District, Jilin, Jilin 132012, China |
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| SubjectTerms | Electricity distribution Graphs Hyperplanes Knowledge representation News Semantics Triplets |
| Title | Research on the Knowledge Representation Method of Power News Text Based on Time Hyperplane |
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