Improving text classification using text summarization

Abdelkader Kaddour, Nassim Zellal, Lamri Sayad
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Abstract

The classification problem has been widely studied in data mining, machine learning, and information retrieval communities with applications in several domains, such as target marketing, medical diagnosis, newsgroup filtering, and document organization. In this work, we take up the challenge of improving Text Classification (TC) using Text Summarizing (TS).
使用文本摘要改进文本分类
分类问题在数据挖掘、机器学习和信息检索社区中得到了广泛的研究,在目标营销、医疗诊断、新闻组过滤和文档组织等多个领域都有应用。在这项工作中,我们提出了使用文本摘要(TS)改进文本分类(TC)的挑战。
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