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Domain specific syntax based approach for text classification in machine learning context

机译:机器学习上下文中基于领域特定语法的文本分类方法

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Due to the vast amount of data, searching and obtaining relevant information on the web is a challenging task. Despite that a broad range of classification techniques have been proposed to improve the information retrieval methods, many difficulties are still present because of the continuous increase in the amount of web contents, as well as its diversity. In this paper, we propose a method that automatically identifies and classifies user queries by using a domain specific syntax approach — this approach is based on the syntactical pattern of each type of search query. A framework is developed to test the performance of the proposed method. Experimental results show that our approach leads to accurate identification of different query types.
机译:由于海量数据,在网络上搜索和获取相关信息是一项艰巨的任务。尽管已经提出了各种各样的分类技术来改进信息检索方法,但是由于网页内容的数量及其多样性的不断增加,仍然存在许多困难。在本文中,我们提出了一种使用领域特定语法方法自动识别用户查询并对其进行分类的方法-该方法基于每种类型的搜索查询的句法模式。开发了一个框架来测试所提出方法的性能。实验结果表明,我们的方法可以准确识别不同的查询类型。

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