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APPLICATION OF DATA MINING ALGORITHM IN INTELLIGENCE ANALYSIS OF ENTERPRISE ECONOMIC INTELLIGENCE

机译:数据挖掘算法在企业经济智能智能分析中的应用

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摘要

With the continuous development and application of high-speed information technology such as the Internet, the acquisition and utilization of economic intelligence has an important impact on the operation of the national economy and the operation of enterprises. Based on the detailed analysis of data mining algorithms, this paper constructs a user classification model based on clustering algorithm and a user interest feature extraction model based on UR-LDA, and uses the improved K-means algorithm in an unsupervised manner. User clustering was carried out, and data mining experiments were conducted on users of Sina Weibo. The experimental results show that the user data extracted from the interest feature topic is clustered by the improved K-means, and six similar user clusters are obtained. The better clustering results are obtained, which indicates that the classification model constructed in this paper is effective.
机译:随着互联网等高速信息技术的持续发展和应用,经济情报的采购和利用对国民经济的运作和企业运营具有重要影响。 基于数据挖掘算法的详细分析,本文基于聚类算法和基于基于UR-LDA的用户兴趣特征提取模型构建用户分类模型,并利用不经过监督的方式使用改进的K均值算法。 进行了用户聚类,并对新浪微博的用户进行了数据挖掘实验。 实验结果表明,从兴趣特征主题中提取的用户数据由改进的k均值聚集,获得六种类似的用户群集。 获得了更好的聚类结果,这表明本文构建的分类模型是有效的。

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