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A Novel Approach for Text Categorization of Unorganized data based with Information Extraction

机译:基于信息提取的非组织数据文本分类的新方法

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Internet has made a profound change in the lives of many enthusiastic innovators and researchers. The information available on the web has knocked the doors of Knowledge Discovery leading to a new Information era. Unfortunately, most Search Engines provide web content which is irrelevant to the information intended to the browser. Many Text Categorization techniques for web content have been developed, to recognize the given document?s category but failed to make trust worthy results. This paper primarily focuses on web content categorization based on classic summarization technique by enabling the classification at word level. The web document is preprocessed first which involves filtering the content with classical techniques and then is converted into organized data. The organized data is then treated with predefined hierarchical categorical set to identify theexact category.
机译:互联网已经改变了许多热情的创新者和研究人员的生活。网络上可用的信息已经敲开了知识发现的大门,从而开创了新的信息时代。不幸的是,大多数搜索引擎提供的Web内容与旨在提供给浏览器的信息无关。已经开发了许多针对Web内容的文本分类技术,以识别给定文档的类别,但未能取得值得信赖的结果。本文主要关注基于经典摘要技术的Web内容分类,方法是在单词级别启用分类。首先对Web文档进行预处理,这涉及使用经典技术过滤内容,然后将其转换为有组织的数据。然后,使用预定义的层次分类集来处理组织的数据,以标识确切的类别。

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