摘要
节点对,指网络中一条联系及其两端节点的组合。作为信息网络中底层的联系组件,节点对表征最基础的信道,但却难以被直接测度。本文尝试引入删除法,构建节点对的间接测度,并给出分别测量网络整体节点数量(信息存量)和联系权重(信息流量)损失的LN和LS指数,用于挖掘无向网络中的关键节点对。h指数研究科研合作网络的实例显示,删除法挖掘出了该网络中具有组织作用、具有桥梁作用或具有相似结构对等性的各类关键节点对。基于删除法的信息网络间接测度方法,有望促成信息网络联系组件测度研究的新视域。
The flow of information is one of the major values of information. In the evolving information world, nodes are generated by information content and carrier. Meanwhile, links derive from information behaviors and interactions. Then nodes and links construct networks. Such networks present the abstract picture of the real information world. In the previous studies of networks measures, the power-law distribution of nodes in complex networks, the centrality measures in social networks, and h-type networks measures in Library Science all focus on nodes instead of links. However, studying the interactions and relations of information is an important task of information analysis. From the point of view of connection, the most basic components can be expressed as node pairs, a combination of a link and nodes at both ends. In information networks, a node pair usually represents a complete channel, which has significant mining and measuring values. This paper selects node pairs, which are the most basic component of links, as research object and attempts to measure them indirectly. The study will use the ＂deletion algorithm＂, which is common in computer science, to construct the measure method of key node pairs. The general idea is to delete thetargeted node pair in the information networks instead of measuring it directly, then indicators are designed to observe the changes of the whole networks. The degree of change reflects the importance of the node pair, which results in a certain degree of equivalence in the node pairs that have same networks variation. Based on the deletion algorithm, the author proposes the LN and Ls indexes respectively for measuring the numbers of nodes （ information stock） and the loss of link＇s weight （ information flow） in order to find key node pairs in the undirected networks. An example of scientific collaboration network related to the topic of h-index shows that the method has unearthed various types of key node pairs that have similar structural equivalence, playing an organizational role or performing connection functions in the networks. This study suggests that the development of innovative measures is the basis of information networks research. In the meanwhile, the measures of link and its components in information networks are key to measuring the information networks. The indirect measures has provided new ideas for the investigation of links in information networks. The deletion algorithm is just one of the indirect measure methods. It is expected that the combination of direct and indirect measure methods will lead to the complete framework of information network analysis.
出处
《中国图书馆学报》
CSSCI
北大核心
2018年第5期47-58,共12页
Journal of Library Science in China
基金
本文系国家自然科学基金青年项目“h型信息网络测度的机理与实证研究”(编号：71503083)的研究成果之一.
关键词
信息网络
复杂网络
社会网络
节点对
联系测度
Information networks
Complex networks
Social networks
Node pairs
Link measures
