A Clustering Analysis of News Text Based on Co-occurrence Matrix

被引：0
|
作者：
Liu, Shan [1 ]
Fan, Xinyi [1 ]
Chai, Jianping [1 ]
机构：
[1] Commun Univ China, Sch Informat Engn, Beijing, Peoples R China
来源：
PROCEEDINGS OF 2017 3RD IEEE INTERNATIONAL CONFERENCE ON COMPUTER AND COMMUNICATIONS (ICCC) | 2017年
关键词：
component; Co-occurrence matrix; clustering analysis;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, we use the improved TF-IDF formula to calculate the weight of the feature word of News. The keyword extraction takes into account the factors such as the parts of speech of feature words and inverse document frequency (IDF). And the K-core theory is used to determine the range of keywords. This study analyzes the co-occurrence strength of news keywords in a certain period of time, and obtains the cluster analysis of the co-occurrence intensity distance of news keywords. And the clustering results are analyzed in the end. In this paper, the quantitative research methods commonly used in bibliometrics are used in the news field to analyze the news content.
引用
收藏
页码：2281 / 2285
页数：5
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