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App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 9

Semantic enhancement and candidate ranking optimization for context-aware event forecast

Ma Rong1,2,3
Ma Bo1,2,3
Wang Zhen1,2,3
Azmat Anwar1,2,3
Yang Yating1,2,3
Wang Lei1,2,3
1. Xinjiang Technical Institute of Physics & Chemistry, Chinese Academy of Sciences, Urumqi 830011, China
2. University of Chinese Academy of Sciences, Beijing 100049, China
3. Xinjiang Laboratory of Minority Speech & Language Information Processing, Chinese Academy of Sciences, Urumqi 830011, China
DOI: 10.19734/j.issn.1001-3695.2025.03.0026

Abstract

Event Forecasting aims to integrate the event semantic information with structural relationships to precisely forecast future events. To address the issues of insufficient semantic capture and limited external knowledge integration in existing graph neural network methods, this paper proposed a context-aware event forecast method based on semantic enhancement and candidate ranking optimization (SECRO) . The method employed a three-stage framework: firstly, a large language model generated high-quality event node embeddings to address semantic expression deficiencies; secondly, a graph neural network modeled the structural and relational connections among events, generating preliminary prediction results; lastly, a candidate ranking optimization mechanism integrated world knowledge from the large language model, enhancing event prediction accuracy. Experiments on three public datasets show that the method improves mean reciprocal rank (MRR) by 8.34 and 6.84 percentage points over RGCN and SeCoGD respectively, achieving state-of-the-art performance. Extended experimental results further confirm that the method enhances the performance of existing graph-based approaches for event prediction.

Foundation Support

新疆维吾尔自治区"天山英才"科技创新领军人才项目(2022TSYCLJ0046)
新疆维吾尔自治区自然科学基金重点项目(2023D01D17)
新疆维吾尔自治区"天山英才"培养计划(2023TSYCCX0041,022TSYCCX0059)
中国科学院青年创新促进会优秀会员项目(Y2023118,Y2021112)
新疆维吾尔自治区重点研发任务专项(2023B03024)
新疆维吾尔自治区自然科学基金项目(2022D01B207)
新疆维吾尔自治区上海合作组织科技伙伴计划及国际科技合作计划项目(2023E01019)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.03.0026
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 9

Publish History

[2025-05-09] Accepted Paper

Cite This Article

马荣, 马博, 王震, 等. 基于语义增强与候选排序优化的背景感知事件预测方法 [J]. 计算机应用研究, 2025, 42 (9). (2025-05-27). https://doi.org/10.19734/j.issn.1001-3695.2025.03.0026. (Ma Rong, Ma Bo, Wang Zhen, et al. Semantic enhancement and candidate ranking optimization for context-aware event forecast [J]. Application Research of Computers, 2025, 42 (9). (2025-05-27). https://doi.org/10.19734/j.issn.1001-3695.2025.03.0026. )

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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