人工蜂群聚类的多媒体网络舆情数据挖掘

Study on Multimedia Network Public Opinion Data Mining Based on Artificial Bee Colony Clustering

阐述多媒体网络舆情数据分布的图谱结构模型,采用人工蜂群轨迹图谱特征分析方法,构建多媒体网络舆情数据的循环查询模型,通过关键词查询和模式查询方法,进行多媒体网络舆情数据的人工蜂群聚类分析,结合数据存储结构分析和联合参数特征分析方法,进行多媒体网络舆情数据图谱参数融合和聚类,实现多媒体网络舆情数据挖掘。仿真结果表明,采用该方法进行多媒体网络舆情数据的精度较高,图谱辨识能力较好。

This paper expounds the map structure model of multimedia network public opinion data distribution, constructs the circular query model of multimedia network public opinion data by using the artificial bee colony trajectory map feature analysis method, carries out the artificial bee colony cluster analysis of multimedia network public opinion data through keyword query and pattern query methods, and combines the data storage structure analysis and joint parameter feature analysis method, Carry out parameter fusion and clustering of multimedia network public opinion data atlas to realize multimedia network public opinion data mining. The simulation results show that this method has high accuracy and good spectrum identification ability for multimedia network public opinion data.