Abstract
Traditional methods have the problems of low detection accuracy and high recall rate when searching hot news information. Therefore, this paper designs a hot news information discovery and development trend prediction method based on decision tree. On the basis of calculating the weight of user attention parameters, the interference information of user attention parameters is eliminated by decision tree algorithm, and then the data set of user attention parameters is established. Based on this, the feature of news text is extracted as topic vector, and the media attention of news information is calculated. Combined with user attention and media attention, the hot index of news information is calculated. The news with a high hot index is regarded as the discovered hot information, and the news with a fast hot index growth rate is regarded as the predicted hot information. Experimental results show that this method improves the accuracy of news information detection and reduces the recall rate of news information detection.
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