基于朴素贝叶斯算法的社交网络数据挖掘技术研究

近年来,随着互联网技术飞速发展与普及,大量社交网络平台迅速崛起。社交网络平台拉近了日常人际关系,提供了便捷的信息通讯交流通道。同时,针对社交网络平台数据挖掘的技术研究成为不可缺少的网络数据研究领域一部分。现有社交网络数据挖掘技术所采用的传统数据挖掘算法与数据分离模式,存在大数据多元特征条件下,数据挖掘准确度降低、挖掘分类逻辑混乱等现象。针对问题产生根源,提出基于朴素贝叶斯算法的社交网络数据挖掘技术研究。采用基于朴素贝叶斯算法设计的PCIE-FN社交网络数据挖掘平台进行全面化的深入性解决。通过实验证明,提出的基于朴素贝叶斯算法的社交网络数据挖掘技术研究,各项数据满足社交网络数据挖掘日常应用要求。

Social networks based on naive bayes algorithm of data mining technology research

in recent years, with the rapid development and popularization of Internet technology, a large number of social networking platform rapid rise. Closing the daily interpersonal social networking platform, provides the convenient information communication channel. At the same time, in view of the social networking platform for data mining technology research has become an indispensable part of network data field. Existing social network data mining techniques adopted by the traditional data mining algorithm and data separation model, there are multiple characteristics under the condition of big data, data mining classification logic chaos phenomenon such as lower accuracy and mining. Roots in view of the problem, based on naive bayes algorithm of social network data mining research. Based on naive bayes algorithm design PCIE - FN social network platform to provide solution to comprehensive data mining. Experiments show that the proposed social networks based on naive bayes algorithm data mining technology research, all data for social network data mining application requirements.