| 邵鹏,邱小洁.多维评价视角下我国生成式人工智能服务关键共性技术识别研究[J].情报工程,2026,(1):017-028 |
| 多维评价视角下我国生成式人工智能服务关键共性技术识别研究 |
| Research on the Identification of Key Generic Technologies in China's Generative Artificial Intelligence Services from a Multi-Dimensional Evaluation Perspective |
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| DOI： |
| 中文关键词: 生成式人工智能服务；大模型；关键共性技术；社会网络分析；LDA 主题模型 |
| 英文关键词: Generative Artificial Intelligence Services; Large Models; Key Generic Technologies; Social Network Analysis; LDA |
| 基金项目:陕西省教育厅科学研究计划青年创新团队项目“陕西省产业链创新联合体合作网络特征与政策促进机制研究”（24JP062）；西安工程大学学位与研究生教育综合改革研究与实践重点项目“生成式人工智能在研究生创新能力培养中的应用研究”（24yjzg10）。 |
| 作者 | 单位 | | 邵鹏 | 西安工程大学管理学院 西安 710048 | | 邱小洁 | 西安工程大学管理学院 西安 710048 |
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| 中文摘要: |
| [目的/意义]生成式人工智能作为新一代信息技术的核心驱动力，正在深刻改变全球科技竞争格局。[方法/过程]基于国家网信办发布的生成式人工智能服务备案信息，采用LDA 模型识别专利技术主题，构建包括通用性、效益性、关联性、稳创性和重要性五个维度的关键技术主题量化指标，借助统计分析、社会网络分析方法对我国生成式人工智能服务关键共性技术进行识别。[结论/结果]我国生成式人工智能服务包括28 个技术主题，其中大模型训练与优化、用户对话与意图识别、语音文本识别与合成、图像生成与处理是我国生成式人工智能服务领域的关键共性技术主题。研究发现对我国生成式人工智能服务技术发展提供了参考依据，为关键共性技术的识别提供了研究方法。 |
| 英文摘要: |
| [Purpose/Significance] As a core driving force of the new generation of information technology, generative artificial intelligence is profoundly reshaping the global landscape of technological competition. [Method/Process] Based on the filing information of generative artificial intelligence services released by the Cyberspace Administration of China, this study applied the LDA model to identify patent technology topics. The paper constructed a quantitative indicator system for key technology topics, including five dimensions: generality, benefit, relevance, stability, and importance. Statistical analysis and social network analysis examined key generic technologies in China’s generative artificial intelligence services. [Result/Conclusion] The study identifies 28 technology topics in China’s generative artificial intelligence services, among which large model training and optimization, user dialogue and intent recognition, speech-text recognition and synthesis, and image generation and processing are identified as key generic technology topics. The findings provide a reference for the development of generative artificial intelligence service technologies in China and offer a research methodology for identifying key generic technologies. |
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