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新一代网络环境下,用户与信息之间的交互耦合及其动态演化更加突出,并基于此形成了多样及多变的用户群组和信息群组。为了提高网络信息共享、传输及获取的效率,需要揭示用户与信息间的耦合及演化机制。本研究主要探讨其耦合机制的研究范式,尝试基于社会网理论揭示用户与信息间的耦合影响机制;基于概率图模型及多主体仿真揭示用户与信息间的关联演化机制;基于社会网理论构建用户群组和信息群组的模式识别模型。用户与信息间的耦合及演化机制的揭示,可丰富行为经济学、复杂性科学以及图书情报档案学等领域的相关理论,用户群组与信息群组模式识别模型的构建,有助于提高网络信息的社会化获取及个性化服务的效率。
Under the new generation of network environment, the interaction coupling between users and information and their dynamic evolution are more prominent, and based on this, diverse and changing user groups and information groups are formed. In order to improve the efficiency of network information sharing, transmission and acquisition, it is necessary to reveal the coupling and evolution mechanism between users and information. This study mainly explores the research paradigm of its coupling mechanism, attempts to reveal the mechanism of the coupling between users and information based on social network theory, reveals the mechanism of the association and evolution between users and information based on the probability graph model and multi-agent simulation, and constructs the users based on social network theory Pattern recognition models for groups and groups of information. The coupling between users and information and the revealing of the evolution mechanism can enrich the relevant theories in the field of behavioral economics, complexity science and library information archives, the construction of user groups and information group pattern recognition models, and help to improve the network Social access to information and personalized service efficiency.