Mining Text Classification Rules Based on Weighted Frequent Itemsets

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Mining Text Classification Rules Based on Weighted Frequent Itemsets

更新时间：2023-11-28

- Mining Text Classification Rules Based on Weighted Frequent Itemsets
- Advanced Engineering Sciences Vol. 40, Issue 6, Pages: 110-114(2008)
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邱江涛,唐常杰,乔少杰.基于加权频繁项集的文本分类规则挖掘[J].工程科学与技术,2008,40(6):110-114.

Mining Text Classification Rules Based on Weighted Frequent Itemsets. [J]. Advanced Engineering Sciences 40(6):110-114(2008)
邱江涛,唐常杰,乔少杰.基于加权频繁项集的文本分类规则挖掘[J].工程科学与技术,2008,40(6):110-114. DOI：

Mining Text Classification Rules Based on Weighted Frequent Itemsets. [J]. Advanced Engineering Sciences 40(6):110-114(2008) DOI：

摘要

中文摘要: 针对特征向量分量的权重和文本大小对分类规则产生的影响，提出一种可以提高关联文本分类性能的文本分类规则挖掘方法，提出了加权频繁项集的概念和相应的加权频繁项集挖掘算法，在分类规则中突出特征向量权重大的向量分量；提出一种特征向量预处理方法，消除文本大小对挖掘分类规则的影响。实验表明，解决上述两个问题将可以很好的提高文本分类的性能。

Abstract

Abstract:The size of text and weight of elements in feature vectors may affect text classification rule. In order to improve the classification accuracy

new concepts of the weighted frequent items and a weighted frequent item set mining algorithm to highlight great weight items were proposed. A pre-processing method for feature vectors was proposed to eliminate ill effects of the size of text on generating classification rules. Experiments demonstrated utility and feasibility of the method.

关键词

关联规则文本分类加权频繁项集

Keywords

association ruletext classificationweighted frequent itemsets

references

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西南财经大学经济信息工程学院四川

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