A Clustering Analysis Of News Text Based On Co-Occurrence Matrix

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.