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Research of web recruitment information extraction based on NLU

机译:基于NLU的网络招聘信息提取研究

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With the rapid development of Internet technology, network has become main source of recruitment information. How to extract the useful recruitment information automatically from these recruitment websites is an important subject nowadays. This thesis studied processing the half-structure text by Natural Language Understanding and improved the existing language model to realize Chinese named entity recognition. Based on this, the author designed a web recruitment information extraction system. The system has a good extensibility and adaptability and precision and recall can reach above 70%.
机译:随着Internet技术的飞速发展,网络已成为招聘信息的主要来源。如今,如何从这些招聘网站上自动提取有用的招聘信息是一个重要的课题。本文研究了通过自然语言理解来处理半结构文本,并改进了现有的语言模型以实现中文命名实体识别。基于此,作者设计了一个网络招聘信息提取系统。该系统具有良好的扩展性,适应性和准确性,召回率可达到70%以上。

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