计算机工程与应用2026，Vol.62Issue(10)：26-53,28.DOI:10.3778/j.issn.1002-8331.2505-0279
知识图谱与推荐算法任务优化及领域应用发展综述
Overview of Task Optimization and Domain Application Development of Knowledge Graph and Recommendation Algorithm
摘要
Abstract
As the core technology of current information filtering,recommendation algorithms need to solve the problems of information fragmentation and insufficient interpretability through semantic association of knowledge graphs and struc-tured knowledge.In order to further promote the technological integration of knowledge graph and recommendation algo-rithm,research the key to improve the performance of recommendation models and the development of multi-domain and multi-technology,this paper decomposes the process of combining knowledge graph with recommendation algorithm into three parts:knowledge graph module optimization,recommendation task module optimization,and multi-task module optimization.The paper comprehensively reviews the relevant theories and research results of each module from the per-spectives of development history,optimization and improvement,core technology,etc.Simultaneously,catering to the current development trends in the field,the latest developments and challenges in the applications of large language models,medicine and e-commerce fields are summarized.Finally,a summary and outlook is provided on the existing problems of knowledge graphs and recommendation algorithms,providing new ideas for future research.关键词
知识图谱/推荐算法/多任务学习/大语言模型Key words
knowledge graph/recommendation algorithm/multi-task learning/large language models分类
信息技术与安全科学引用本文复制引用
韩一鸣,魏国辉..知识图谱与推荐算法任务优化及领域应用发展综述[J].计算机工程与应用,2026,62(10):26-53,28.基金项目
国家自然科学基金(61702087) （61702087）
山东省自然科学基金面上项目(ZR2022MH203) （ZR2022MH203）
山东省研究生优质教育教学资源项目(SDYKC2023044) （SDYKC2023044）
山东中医药大学教育教学研究课题(实验教学专项)(SYJX2022013). （实验教学专项）
