Review on Construction and Application of Domain Knowledge Graphs: Cross-Domain Practices and Cutting-Edge Explorations Driven by Large Language Models

Knowledge graphs (KGs) are core infrastructure for artificial intelligence, and large language models (LLMs) have significantly advanced their construction and application. This paper systematically reviews the latest domestic and international research on domain KG construction. Domestically, studies focus on low-resource adaptation and prompt engineering in vertical fields (agriculture, healthcare, education, etc.), such as few-shot extraction via LoRA and zero-shot entity recognition with DeepSeek. Internationally, research emphasizes general frameworks in mineral resources, smart manufacturing, and other areas, including multimodal fusion with Cross-Modal Transformers and quintuple-based knowledge representation. It further analyzes technological evolution and existing challenges. Future directions include deepening LLM-KG synergy and enhancing interpretability. This study provides a systematic reference for intelligent knowledge management.