物联网学报2026，Vol.10Issue(1)：150-160,11.DOI:10.11959/j.issn.2096-3750.2026.00406
基于深度强化学习的图约简方法
Graph reducing method based on deep reinforcement learning
摘要
Abstract
The development wave of general artificial intelligence drives the generation and processing of massive data,and large-scale and heterogeneous graph data networks constitute an important foundation of the digital world.However,the continuously growing scale of data not only increases the difficulty of graph data processing,but also creates the need to reduce graph size and maximize the amount of graph information.Existing methods make it difficult to synergistically control the graph size and optimize the amount of graph information,which limits the effectiveness of graph data analysis and processing.In response to the need for balanced control of graph data scale and information content,the graph reduc-ing problem with scale regulation as the constraint and information maximization as the goal was proposed.Specifically,a graph fusion algorithm and a deep reinforcement learning-based graph reducing algorithm were designed to solve the problem,including graph reducing operations such as node fusion,composite mapping,and methods used for similarity metrics.Experiments verified the balanced regulation ability of the reducing algorithm,and comparisons with four algorithms across three evaluation metrics—feature similarity,graph similarity,and edge information loss—showed that the proposed graph reduction method could achieve performance improvements of at least 20.7%,19.9%,and 26.3%,respectively.关键词
图约简/深度强化学习/规模调控/信息量/相似性Key words
graph reducing/deep reinforcement learning/scale regulation/amount of information/similarity分类
信息技术与安全科学引用本文复制引用
陈根鑫,亓晋,刘娅利,高钰,董振江,孙雁飞..基于深度强化学习的图约简方法[J].物联网学报,2026,10(1):150-160,11.基金项目
国家自然科学基金面上项目(No.62172235) （No.62172235）
江苏省重点研发计划项目(No.BE2023025) （No.BE2023025）
江苏省高等学校基础科学(自然科学)研究项目(No.22KJB520028,No.22KJB520026) The General Program of the National Natural Science Foundation of China(No.62172235),The Primary Re-search and Development Plan of Jiangsu Province(No.BE2023025),The Natural Science Research Project of Jiangsu Higher Educa-tion Institutions(No.22KJB520028,No.22KJB520026) （自然科学）
