Research and application of news-text similarity algorithm based on Chinese word segmentation

Wei Guan, Pengzhou Zhang
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引用次数: 3

Abstract

With the rapid development of the Internet, text messages on the network is also an exponential growth. Facing the vast network of information, how to quickly and efficiently identify the different sites of similar news-text plays a major role in strengthening the integrated management of network information. Existing text similarity algorithm has many disadvantages when used in Chinese news-texts, we propose a more suitable and effective news-text similarity algorithm. This paper uses the Chinese word segmentation technology, and based on this kind of news-text similarity comparison and improved vector space model is applied to the algorithm. Experimental results show that the proposed method is superior to traditional methods the results obtained, thus proving the proposed Chinese news-text similarity calculation method.
基于中文分词的新闻文本相似度算法研究与应用
随着互联网的飞速发展,网络上的短信也呈指数级增长。面对庞大的信息网络,如何快速有效地识别相似新闻文本的不同站点,对于加强网络信息的综合管理具有重要意义。现有的文本相似度算法在中文新闻文本中存在许多不足,本文提出了一种更合适、更有效的新闻文本相似度算法。本文采用中文分词技术,并在此基础上对新闻文本相似度进行比较,并将改进的向量空间模型应用到算法中。实验结果表明,本文提出的方法优于传统方法得到的结果,从而验证了本文提出的中文新闻-文本相似度计算方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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