| 基于文本聚类的LSI文本分类模型 |
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| 引用本文： | 邱志宇,安艳辉.基于文本聚类的LSI文本分类模型[J].河北师范大学学报(自然科学版),2012,36(1):24-26,83. |
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| 作者姓名： | 邱志宇 安艳辉 |
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| 作者单位： | 1. 河北师范大学数学与信息科学学院,河北石家庄,050024
2. 河北省工业和信息化厅,河北石家庄,050071 |
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| 摘 要： | 文本自动分类是文本挖掘的基础,可广泛地应用于信息检索,web挖掘等领域.在分类前首先要将文本表示成计算机能处理的形式,提出了一种将隐含语义索引(LSI)与文本聚类相结合的中文文本自动分类的方法.在挖掘文本的语义信息,提高分类速度上均取得了较好的效果.通过实验验证了方法的有效性.
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| 关 键 词： | 文本分类 隐含语义检索 文本聚类 |
The Model of Text Categorization Based on Latent Semantic Indexing |
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| QIU Zhiyu
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AN Yanhui.The Model of Text Categorization Based on Latent Semantic Indexing[J].Journal of Hebei Normal University,2012,36(1):24-26,83. |
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| Authors: | QIU Zhiyu AN Yanhui |
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| Institution: | 1.College of Mathematics and Information Science,Hebei Normal University,Hebei Shijiazhuang 050024,China;2.Industry and Information Technology Department of Hebei Province,Hebei Shijiazhuang 050071,China) |
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| Abstract: | Text categorization(TC),the foundation of text mining,can be used in information retrieval and web data mining.Before text categorization the text should be converted to a model that can be processed in computer at first.A new algorithm that combines latent semantic indexing(LSI) and text clustering is given.Through the experiment this algorithm is fouhe effective. |
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| Keywords: | text categorization latent semantic indexing text clustering |
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