社交网络中热点话题深度挖掘方法及实验测试

互联网大数据时代,社交网络数据交互具有实时性、社会性、复杂性。多元架构数据信息中会存在热点话题数据。传统社交网络热点话题挖掘方法存在热点词条检索速度慢、话题词条层浅、断层数据无法挖掘等一系列问题,如何将社交网络中的热点话题数据进行挖掘,针对这一问题提出大数据信息词条特征比对提取方法,对社交网络中的大数据数据信息词条进行特征显化处理,采用饼图对比方式对特征化词条数据进行网络互交频率展现,采用多维数据获取法,解决社交网络热点话题挖掘中出现的数据阻滞现象,满足社交网络中热点话题深度挖掘的要求。通过仿真实验对提出方法进行效率、准确度、速度测试,实验结果表明,提出方法对社交网络中的热点话题挖掘快捷、高效、实用性强。

Depth of the hot topics in social network mining method and experimental test

The Internet era of big data, social network data interaction is real-time, sociality, complexity.Multiple architecture data information are hot topics in data.Traditional social network hot topic mining methods retrieval speed slow, hot entry subject terms and shallow layer, fault data cannot be mining and so on a series of problems, how to social network hot topic in data mining, in order to solve this problem put forward comparing large data entry feature extraction method, the social network of big data features manifest data entry, and the pie chart can be compared to the way of network intercrossing frequency characteristic entry data show, the multidimensional data acquisition method, solve the hot issues of social network in the mining of the data block phenomenon, to meet the requirements of the hot topics in social network depth excavation.Through the simulation experiments on the proposed method efficiency, accuracy and speed test, the experimental results show that the proposed method is the hot topic in social network mining fast, efficient and practical.