Microblogging User Tag Prediction Based on Bayesian

Guoqiang Gao, Ruixuan Li
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Abstract

In the social network, to users, the tag is an important basis to mark and classify the resource. The tag of microblogging users can be used for advertising and network marketing. This paper presents a method based on naive Bayesian to predict the user tag. We use the user's basic attributes and some popular public tags as the features in Bayesian to predict whether a public tag belongs to a user. The experimental results show that the proposed method can achieve 87% accuracy.
基于贝叶斯的微博用户标签预测
在社交网络中,对于用户来说,标签是对资源进行标记和分类的重要依据。微博用户的标签可以用于广告和网络营销。提出了一种基于朴素贝叶斯的用户标签预测方法。我们使用用户的基本属性和一些流行的公共标签作为贝叶斯中的特征来预测公共标签是否属于用户。实验结果表明,该方法的准确率达到87%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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