An Identification Method of News Scientific Intelligence Based on TF-IDF

Lu Pan, Haibo Tang, Lei Zhou, Liuyang Wang, Quanyin Zhu
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引用次数: 4

Abstract

With the development of Internet, the amount of Information has been rapidly growing which is spread widely. In order to improve the value and accuracy of science information that is pushed in this paper, an intelligence dichotomous method for science information categorization to identify science information from massive Web news is presents. During the experiment, 85.3% recognition rate of the recognition non-tech news are realized and 82.9% accuracy rate, the results show that the method can effectively identify Web science information news and reduce the amount of independent news.
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基于TF-IDF的新闻科学智能识别方法
随着互联网的发展,信息的数量迅速增长,传播广泛。为了提高推送的科学信息的价值和准确性,本文提出了一种基于智能二分法的科学信息分类方法,从海量网络新闻中识别科学信息。实验中,非科技新闻的识别识别率达到了85.3%,准确率达到了82.9%,结果表明该方法能够有效地识别Web科学信息新闻,减少了独立新闻的数量。
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