基于社区检测启发式模型的技术创新趋势感知

Hecan Zhang, Xin Guo, C. Yi, Yue Dou, Dong Chen, Nannan Tong, Jiandong Wang
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引用次数: 0

摘要

专利分析被广泛应用于竞争情报分析、技术趋势感知、产业布局规划、宏观经济调控等研究领域。基于专利数据,本文提出了一种基于启发式社区检测模型的技术创新趋势感知算法PeTIT。PeTIT算法包括专利本体提取、技术创新树构建、技术创新社区检测和技术创新趋势感知四个步骤。我们在2000年6月1日至2019年5月1日的中国人工智能领域发明专利真实数据集上实现了PeTIT算法。结果表明,人工智能的创新情况主要集中在10个领域。此外,智能驾驶应用领域已成为发展最快的产业之一。最后,实验结果表明,三次指数平滑模型在感知技术创新趋势方面具有较高的性能。
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PeTIT: Perceiving the Technological Innovation Trends via the Heuristic Model of Community Detection
Patent analysis is widely used in many kinds of research, such as competitive intelligence analysis, technology trends perceiving, industrial distribution planning, macro-economy regulations, and so on. Based on the patent data, this paper proposed a novel algorithm, which named PeTIT, to perceive the technological innovation trends by applying the heuristic community detection model. The PeTIT algorithm included four steps: patent ontology extraction, technological innovation tree construction, technological innovation community detection, and technological innovation trends perceiving. We implemented the PeTIT algorithm on the real dataset of invention patents in the field of artificial intelligence in China, which ranged from Jun 1st, 2000 to May 1st, 2019. The results showed that the innovation situation of artificial intelligent was mainly concentrated in 10 fields. Moreover, the application field of intelligent driving has become one of the fastest-growing industries. Finally, the experimental results demonstrated that the cubic exponential smoothing model had a higher performance by perceiving the technological innovation trends.
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