文章摘要

张斌,李亚婷.知识网络演化模型研究述评[J].中国图书馆学报,2016,42(5):85~101
知识网络演化模型研究述评
A Review of the Evolution Model of Scientific Knowledge Network
投稿时间:2016-05-18  修订日期:2016-07-12
DOI:10.13530/j.cnki.jlis.165006
中文关键词: 知识网络  演化模型  引证网络  合作网络  链路预测
英文关键词: Knowledge network  Evolution model  
基金项目:本文系国家自然科学基金面上项目“知识网络的形成机制及演化规律研究”(编号:71173249)和国家自然科学基金重点国际(地区)合作研究项目“大数据环境下的知识组织与服务创新研究”(编号:71420107026)的研究成果之一
作者单位E-mail
张斌 武汉大学信息资源研究中心 湖北 武汉 430072。 zb0205@126.com 
李亚婷 武汉大学信息资源研究中心 湖北 武汉 430072。  
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中文摘要:
      知识网络演化模型可用于探讨和发现知识发展脉络的关键特征,相关研究主要集中在统计物理、计算机、图书情报等领域。本文对网络模型经典理论进行回顾,从引证网络和合作网络两个方面对具有代表性的演化模型进行梳理,介绍网络演化模型评价的一些进展,最后提供了一个相对清晰的研究框架。研究发现:针对这方面的研究近年来有成为图书情报学领域研究热点的趋势;已有引证网络和合作网络的研究大多利用BA模型及其改进模型来研究演化机理;未来的研究应结合网络的局部结构特征和节点的外部属性信息来建立混合择优模型;众多知识网络演化模型在解释真实网络演化时,依然存在着不小差距,利用链路预测的原理来设计和评价演化模型有望成为一个新的研究方向。图2。参考文献79。
英文摘要:
The evolution model of knowledge network is an abstract expression of knowledge networks inherent interaction mode and process,a method to explore the key features of knowledge development and a bond to connect the external structure with internal interaction mechanism.Currently,researches on this issue are scattered in the fields of Statistical Physics,Computer Science,and Library & Information Science. It has become a research hotspot in Library & Information Science in recent years.Knowledge network is the product of knowledge exchange,and both classic citation network and co authorship network are dominant representations for it. Many scholars studied citation network and co authorship network to explore the interaction among scholars,collaboration evolution mechanism,knowledge dissemination and development from the perspective of network evolution.
Library & Information Science has long been concerned about the evolution model of knowledge network.Early Price Model laid the ideological foundation for BA scale free network discovery. As knowledge network has small world structure and scale free characteristic,growth mechanism and preferential attachment mechanism are essential to understanding its formation and evolution. Citation network can reflect the flow and the inheritance relation of knowledge clearly. Moreover,temporal and spatial factors and nodes heterogeneity can affect its preferential attachment mechanism,and function expression of new nodes and edges can help simulate its growth mechanism. By the appropriate modification,these factors can also be used for co authorship network.
Co authorship network reflects the collaboration relationship among knowledge creators. Based on co authored papers,this kind of network has important significance in understanding the pattern of knowledge exchange and the establishment of interdisciplinary collaboration. Similarity based algorithms can help examine the link prediction effect of co authorship network and effectively identify the main influence factors on connection,which lays the foundation for the construction of evolution model. Most current researches still use BA Model and its improvements to study evolution mechanism. A future important research direction would be adding some external attributes of nodes to build hybrid preferential attachment model. As scientific collaboration contains knowledge exchange process,analysis ideas based on scientific research team evolution or network co evolution can help identify the dynamic factors of the evolution and discover the scientific knowledge diffusion rules.
Many evolution models of knowledge network still have some bias when explaining the evolution of the real network,which leads to the future direction of evaluating network models. Compared to the traditional method which directly analyzes the features of the network structure,the method that uses link prediction to evaluate is more complicated,and applies more advanced mathematical knowledge,yet it is more convincing in the quantitative comparison level.In the future research,the evolution model and link prediction should be integrated into one research framework,such as:1) When the network evolution mechanism is unclear,the main features that affect the network connection can be found through statistical analysis of the real world network and observation of link prediction; 2) Based on these features and the previous research findings,the evolution model of the specific network can be constructed,evenits implied rules can be revealed; 3) Use link prediction to design a quantitative evaluation method,which can evaluate advantages and disadvantages of the constructed network model and its evolution mechanism. 2 figs. 79 refs.
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