Journal of Engineering, Project, and Production Management, 2027, 17(2), 2025-345
Knowledge-Enhanced Semantic Reasoning Model for Implicit Sentiment Recognition
1 Instructor,
School of Foreign Languages, Shandong University of Political Science
and Law, Jinan, 250014, China, E-mail: sunyuhui37@163.com
2 Instructor, School of Foreign
Studies, Shandong University of Finance and Economics, Jinan, 250014,
China, E-mail: FengTianzz@outlook.com (corresponding author).
Project Management
Received December 19, 2025; revised February 3, 2026; April 1, 2026; June 25, 2026; accepted July 2, 2026
Available online July 12, 2026
Abstract: Existing methods for implicit sentiment identification in think tank documents face limitations in deep semantic understanding, including insufficient integration of domain knowledge and difficulty in modeling sentiment evolution in long texts. This study proposes an implicit sentiment recognition model that combines knowledge enhancement with semantic reasoning. The model builds a foundation for deep semantic understanding through a bidirectional encoder and enhances the modeling of implicit sentiment dependencies in text by combining the graph convolutional network’s graph-structured reasoning mechanism. In metric tests, the model achieves 95.92% accuracy in implicit sentiment classification with 97.58% domain adaptability. The model also demonstrates strong performance in long-document sentiment modeling (96.87% accuracy) and cross-domain consistency (0.971). Based on the experimental evaluation, the model developed in this paper achieves superior performance compared with existing approaches in testing, while alleviating the limitations of implicit sentiment extraction and biases in domain-specific term comprehension observed in current methods, thereby offering valuable support for in-depth semantic analysis and decision-making in think tank documents.
Keywords: Bidirectional encoder; graph convolutional network; implicit emotion recognition; knowledge enhancement; semantic reasoning; think tank document.
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Citation: Sun, Y., and Tian, F. (2026). Knowledge-Enhanced Semantic Reasoning Model for Implicit Sentiment Recognition. Journal of Engineering, Project, and Production Management, 17(2), 2025-345.
