Innovation Oriented Hyper Model and Evolution of Knowledge Network

Jian Xie, Lin Gong, Zijian Zhang, Yan Yan, Sheng Tang
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Abstract

Aiming at the topological characteristics and unclear innovation of knowledge network, a hyper model for knowledge was established. Based on the model, the keyword network and its evolution model were constructed with a newly-raised concept called innovation degree which measures the innovation in specific knowledge field. After that, specific model was constructed and its evolution was analyzed through papers from the field of artificial intelligence, which verified that the topological structure presented small-world nature and the innovation degree were effective in identifying the direction of knowledge innovation in relevant fields.
面向创新的超模型与知识网络演化
针对知识网络的拓扑特性和创新不明确的特点,建立了知识网络的超模型。在此基础上,构建了关键词网络及其演化模型,并提出了衡量特定知识领域创新程度的创新度概念。之后,通过人工智能领域的论文构建了具体的模型,并对其演化进行了分析,验证了拓扑结构呈现小世界性质,创新程度对识别相关领域知识创新方向是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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