情报杂志2025，Vol.44Issue(7)：106-113,164,9.DOI:10.3969/j.issn.1002-1965.2025.07.014
基于网络嵌入与深度学习的潜在竞争对手识别
The Identification of Potential Competitors Based on Network Embedding and Deep Learning
摘要
Abstract
[Research purpose]Identifying and monitoring competitors is a key aspect of a firm's success in a highly dynamic competitive environment.With the development of cross-border integration of industries,the competitive relationship between enterprises has become more and more complex and hidden,and organizations from across the border are likely to become important competitors,and such"in-visible"competitors are often difficult to identify.Therefore,this study proposes a two-stage competitor identification model based on net-work embedding and deep learning to accurately identify potential competitors of enterprises.[Research method]Based on the patent ci-tation relationship,technology similarity relationship,and product and service supply relationship among the enterprises listed on China's A-share Science-Based Innovation Board,a multi-source heterogeneous network is constructed,and node features,such as multiple linka-ges,are extracted from the network through the GATNE network embedding method,and a deep neural network model is applied to de-duce the potential competitive relationship.[Research result/conclusion]As verified by the empirical analysis of A-share Science and Technology Innovation Board listed companies,GATNE-DNN method has a greater advantage over other methods in potential competitor identification,which is helpful for enterprises to effectively identify potential competitors.关键词
竞争对手识别/网络嵌入/深度学习/深度神经网络/多源异构网络Key words
competitor identification/network embedding/deep learning/deep neural networks/multi-source heterogeneous network分类
社会科学引用本文复制引用
许冠南,陈璐璐,康宁,孔德婧,牟显忠..基于网络嵌入与深度学习的潜在竞争对手识别[J].情报杂志,2025,44(7):106-113,164,9.基金项目
国家自然科学基金面上项目"数智创新生态系统嵌入对企业创新的作用机制研究:基于多重网络子群视角"(编号:72272017) （编号:72272017）
国家社会科学基金重点项目"数字经济推动新兴产业创新的制度逻辑与系统构建研究"(编号:22AZD125) （编号:22AZD125）
北京社会科学基金重点项目"北京国际科技创新中心建设的产业生态韧性优化与治理研究"(编号:22GLA012) （编号:22GLA012）
北京市自然科学基金面上项目"产业融合视角下智能服务创新机制研究——基于多源知识图谱"(编号:9232015) （编号:9232015）
北京邮电大学"双一流"建设学科交叉团队项目"2023双一流提升自主大数据与创新治理学科交叉团队"(编号:2023SYLTD11)研究成果. （编号:2023SYLTD11）
