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Text Analysis and Knowledge Mining

机译:文本分析与知识挖掘

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摘要

As the use of IT systems expands, growing amounts of textual data are being generated, stored, and searched. This trend is widely believed to be causing information overload. Although the increase of accessible data is intended to increase our knowledge and yield insights for better actions, the data glut is making it hard to find meaning. Natural Language Processing (NLP) is a key technology to exploit text data, so applications for NLP are increasing rapidly. Such applications often exploit text mining [1], [2], but they involve a broad range of NLP technologies as the applications develop. This new trend is generating new demands for NLP that require more research.
机译:随着IT系统的使用展开,正在生成,存储和搜索越来越多的文本数据。这种趋势被广泛认为导致信息过载。虽然可访问数据的增加旨在提高我们的知识和屈服洞察力,但数据呈现,难以找到意义。自然语言处理(NLP)是利用文本数据的关键技术,因此NLP的应用程序正在迅速增加。此类应用程序经常利用文本挖掘[1],[2],但它们涉及广泛的NLP技术,因为应用程序的发展。这种新趋势正在为需要更多研究的NLP产生新的需求。

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