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App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 2

Solving ontology matching through genetic programming algorithm based on dynamic output node selection

He Guodong1
Lyu Qing1
Xue Xingsi2
1. College of Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan 030024, China
2. College of Computer Science and Mathematics, Fujian University of Technology, Fuzhou Fujian 350118, China
DOI: 10.19734/j.issn.1001-3695.2025.07.0241

Abstract

Genetic Programming (GP) is an effective method for solving ontology matching problems. However, due to the vast search space of ontology matching tasks, fixed root node outputs in GP cannot efficiently obtain high-quality matching results. To enhance the algorithm's search efficiency and improve the quality of matching results, this paper proposed an improved GP with dynamic output node selection. The algorithm introduced a dynamic output node selection mechanism into the GP-based matching process, adaptively determining multiple output nodes for each individual to thoroughly explore the solution space. Additionally, a novel probability distribution-guided selection method guided the selection of individual output nodes. Statistical analysis of the evolutionary information of the population adaptively adjusted the probability distribution, promoting rapid algorithm convergence. Finally, this paper designed position-aware crossover and mutation operators. By considering the positional relationship between the crossover (or mutation) point and elite subtrees in the GP tree, the method employed different breeding strategies to balance global exploration and local exploitation. Experimental results demonstrate that the proposed method can efficiently determine high-quality matching results, outperforming advanced matching methods.

Foundation Support

国家自然科学基金资助项目(62172095)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.07.0241
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 2

Publish History

[2025-10-27] Accepted Paper

Cite This Article

贺国东, 吕青, 薛醒思. 基于动态输出节点选择的遗传规划算法解决本体匹配问题 [J]. 计算机应用研究, 2026, 43 (2). (2025-11-04). https://doi.org/10.19734/j.issn.1001-3695.2025.07.0241. (He Guodong, Lyu Qing, Xue Xingsi. Solving ontology matching through genetic programming algorithm based on dynamic output node selection [J]. Application Research of Computers, 2026, 43 (2). (2025-11-04). https://doi.org/10.19734/j.issn.1001-3695.2025.07.0241. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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