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基于热度曲线分类建模的微博热门话题预测*

DOI: 10.16451/j.cnki.issn1003-6059.201501004, PP. 27-34

Keywords: 热度曲线,分类建模,加权投票,热门话题预测

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Abstract:

及时掌握大众关心的热点话题是企业进行商业创新和商务营销的重要前提.现有方法大都依赖于非结构化数据的处理或反复遍历样本集,使算法复杂性较高.文中从话题的统计特性出发,提出建立在结构化数据上的非参数方法.首先对单个话题构建表征话题传播扩散程度和关注聚焦程度的热度曲线;然后对这些形态丰富的热度曲线进行分类建模,得到不同类别曲线的共性特征及发展规律;最后使用分类模型上的加权投票规则预测新话题是否会发展成为热门话题.基于新浪微博平台进行数据收集和实验,结果表明该方法数据结构简单、效果良好、复杂度低且易于控制.

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