Recent research status and analysis in knowledge mapping for in-depth learning
Selling umbrella one, two in the sahara
1. Guangzhou medical university, college of biomedicine engineering, guangzhou, 511436
2. College of biomedicine engineering, guangdong medical university, lake dong chongshan, 523822
Abstract: knowledge graphs, kgs, as a structured form of knowledge expression, plays an important role in artificial intelligence. In recent years, the integration of in-depth learning techniques with knowledge mapping has made significant progress, particularly in the areas of knowledge mapping embedded, completion, reasoning and integration with large language models (large language models, llms). The present paper provides an overview of the state of research in the knowledge map from 2023 to 2025, covering the main methods, applications and analysis. The focus was on the use of the map neural networks, gnns, transformer models in knowledge mapping missions, and emerging trends such as time-series knowledge mapping, multi-modular knowledge mapping and neurograph reasoning. At the same time, there is an in-depth analysis of current challenges, such as hallucinations, broad-based competencies and computing efficiency, and a vision of future directions, including self-monitoring learning and multi-modular integration applications. Studies have shown that, while in-depth learning has significantly improved the expression and reasoning efficiency of knowledge maps, the issue of knowledge incompleteness and interpretability still needs to be addressed. By introducing tables to compare key model performance, this paper provides a comprehensive framework to guide future research。
Keywords: knowledge mapping; in-depth learning; mapping neural networks; knowledge embedding; knowledge reasoning; large language models; multi-modular integration
Bibliography code: a graph classification number: r318. 0 doi:
Recent researchtrends and analysis of deep learning in knowledge
Zeng, zhenhua 1, 2
1 school of biodical engineering, guangzou medical university, guangzou 511436, china
2. School of biodical engineering, guangdong medical universityNguan 523822, china
As a state of affairs, a civil society, a society, a society, a society, a society, a society, a society, and a societyI don't know what you're talking aboutIf you don't have a chance, you're going to have to take a look at thisNo, no, no, no, noBy introduceting tabular companies of key models, this paper deals with a complex problemI'm sorry.
Keywords: knowledge graph; deep learning; graph neural networks; knowledge embeding; knowledge reasoning; large language models; multimedia fusion
