稀有项在提高基于多项式网络的文本分类性能中的作用

Mayy M. Al-Tahrawi
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引用次数: 7

摘要

本文研究了罕见词和罕见词在多项式网络(PNs)中提高英语文本分类准确率的作用。为了研究罕见词对提高基于PNs的文本分类准确率的影响,在使用PNs的路透社语料库上实验了不同的词约简标准和不同的词加权方案。对每个约简项集上的每个项加权方案进行测试,一次保留罕见项,另一次删除罕见项。本研究的所有实验都表明,无论采用何种术语约简方法、分类使用的术语数量还是采用的术语加权方案,保留罕见术语都能显著提高多项式网络在文本分类中的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Role of Rare Terms in Enhancing the Performance of Polynomial Networks Based Text Categorization
In this paper, the role of rare or infrequent terms in enhancing the accuracy of English Text Categorization using Polynomial Networks (PNs) is investigated. To study the impact of rare terms in enhancing the accuracy of PNs-based text categorization, different term reduction criteria as well as different term weighting schemes were experimented on the Reuters Corpus using PNs. Each term weighting scheme on each reduced term set was tested once keeping the rare terms and another time removing them. All the experiments conducted in this research show that keeping rare terms substantially improves the performance of Polynomial Networks in Text Categorization, regardless of the term reduction method, the number of terms used in classification, or the term weighting scheme adopted.
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