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Hadoop-based Analysis Model of Network Public Opinion and Its Implementation

机译:基于Hadoop的网络舆情分析模型及其实现

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In order to perform network public opinion mining effectively, this paper proposes a Hadoop-based network public opinion analysis model, which applies HDFS file service system to store massive network data distributed, providing fault tolerance and reliability assurance; As the traditional K-means clustering method is too inefficient to process massive data during the clustering process, this paper adopts MapReduce-based K-means distributed topic clustering computation method to process the massive public opinion information through multi-computer cooperation efficiently; And to obtain the information of hot network public opinion in a certain period of time by the analysis of topic heat, and verify the effectiveness of the proposed method by experiments.
机译:为了有效地进行网络舆情挖掘,提出了一种基于Hadoop的网络舆情分析模型,该模型运用HDFS文件服务系统存储海量分布的网络数据,提供了容错性和可靠性保证。由于传统的K-means聚类方法在聚类过程中效率低下,无法有效地处理海量数据,因此本文采用基于MapReduce的K-means分布式主题聚类计算方法,通过多机协同有效地处理海量舆情信息。通过对话题热点的分析,获得一定时间内热点网络舆情信息,并通过实验验证了该方法的有效性。

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