项的权重计算(term weighting)普遍使用的 是 tfidf(term frequency/ inverse document frequency)函数[23],其定义如下: Tr tfidf (t k , d j ) =# (t k , d j ...
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Secondly,The term weighting which is of great importance in LSI is studied in detail, and a new weighting design based on non- linear function and location factor was proposed. The retrieval performance has been improved further.
其次对LSI的重要优化过程——权重计算进行了深入分析,提出了一种基于“非线性函数”和“位置因子”的新权重方案,并对其效果进行了对比验证。
参考来源 - 基于潜在语义索引的中文文本检索研究Moreover, the improved algorithms of term weighting and reduction of dimensionality also show their effectiveness.
实验证明,多层次的分类算法较以往的单层次的分类系统相比,在分类的精度和速度上都有明显的提高,改进的特征加权算法和维数缩减方法也有效地改善了分类器的性能。
参考来源 - 多层次中文文本分类技术的研究·2,447,543篇论文数据,部分数据来源于NoteExpress
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