CCTV News Broadcast Information Mining: Keyword Extraction Based on Semantic Model and Statistics Visualization

Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture Pub Date : 2020-10-15 DOI:10.1145/3421766.3421827

Yujie Xie, Fenghai Liu

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Abstract

CCTV News Broadcast is one of the most popular news programs in China, and it is also the most important propaganda platform in China. CCTV News Broadcast is established to "Improve the quality of publicity", so it is "A product of visual culture of national ideology" and "Taking politics as the standard" is primary appeal. [1] At present, there is little research on the text of CCTV News Broadcast. This paper focuses on the CCTV News Broadcast, using the visualization model based statistics and semantic based keyword extraction model (SKE) to extract the text features of CCTV News Broadcast. It can help the public quickly capture the key information of CCTV News Broadcast. Moreover, this paper also forms a set of Chinese corpus with keywords tagging in the field of CCTV News Broadcast. It provides important data support for machine learning method and subsequent research. In addition, aiming at some important problems found in this paper, this paper proposes further research direction for text data processing in CCTV News Broadcast field.

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CCTV新闻广播信息挖掘:基于语义模型和统计可视化的关键词提取

央视新闻联播是中国最受欢迎的新闻节目之一，也是中国最重要的宣传平台。央视新闻联播是为了“提高宣传质量”而设立的，是“民族意识形态视觉文化的产物”，“以政为本位”是其首要诉求。[1]目前，对央视新闻联播文本的研究较少。本文以央视新闻联播为研究对象，采用基于统计的可视化模型和基于语义的关键词提取模型(SKE)对央视新闻联播的文本特征进行提取。它可以帮助公众快速捕捉到央视新闻联播的关键信息。此外，本文还在央视新闻联播领域形成了一套带有关键词标注的中文语料库。为机器学习方法和后续研究提供了重要的数据支持。此外，针对本文发现的一些重要问题，提出了CCTV新闻直播领域文本数据处理的进一步研究方向。

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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Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture

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