知识网络情绪互信息熵检测

针对互联网知识资源网络中知识层次结构与网民情绪的相互关系问题,为了准确把握知识资源网络的节点结构与情绪过程的关联性,提出情绪信息熵算法.通过构建认知的活动重要度、情绪适用度和情感距离等重要指标,有效地诠释了知识结构层面与情绪过程的适用性,实现了互联网知识资源网络的情绪疏导与知识结构的二元融合.结果表明:情绪信息熵算法能对认知过程和情绪因素进行有效疏导,并能有效促进认知效用,具有较高的实践推广价值.

Emotional mutual information entropy testing of knowledge network

Aiming at the mutual relationship problem between the hierarchical knowledge structure and netizen emotion in the internet knowledge resource network and in order to accurately grasp the relevance between the node structure of knowledge resource network and emotional process, the emotional information entropy algorithm was proposed. Through constructing such important indexes as the cognitive activity importance, emotional applicability and emotional distance, the applicability of both knowledge structure level and emotional process was effectively explained, and the binary fusion of emotional adjustment and knowledge structure in the internet knowledge resource network was achieved. The results show that the emotional information entropy algorithm can effectively guide the cognitive process and emotional factors, can effectively promote the cognitive effectiveness, and has a higher popularized value.