中文摘要：

利用计量思想和方法对知识进行聚合是大数据环境下知识科学发展的重要方向。文章认为知识计量聚合是对科学知识资源系统结构动力学的研究,强调利用计量理论和方法,从知识的内容和语义出发揭示知识内容的层次性、关联系和结构性,最终实现知识服务。多元性和阶段性是知识计量聚合的核心特征,从聚合对象、知识网络、测度层次和目标结构的角度论述了知识计量聚合的多元性特征;元数据—传统计量关联—语义与计量结合的聚合实现过程体现了知识计量聚合的阶段性特征。最后,对知识计量聚合研究中的新命题进行了讨论。

英文摘要：

Knowledge aggregation based on the theory and methods of informetrics is a new trend for knowledge science in big data environment. This paper defines the metric-based knowledge aggregation as a research on structural dynamics of knowledge re- sources system. The metric-based knowledge aggregation focuses on revealing the hierarchy, correlation and structure of knowledge through semantics. The goal of metric-based knowledge aggregation is for knowledge services. The paper discusses the diversity fea- tures of metric-based knowledge aggregation from 4 perspectives, including object, knowledge network, measurement level and purpose. The stage feature of metric-based knowledge aggregation is also revealed by observing aggregations from metadata, informe- trics relationships and semantic-metric combined aggregation. Finally, the paper concludes the research and discusses some new re- search issues of metric-based knowledge aggregation.