Weighted classification method for disaster information importance of blog articles based on deep learning and XGBoost algorithm

Abstract

The invention discloses a weighted classification method for disaster information importance of blog articles based on deep learning and XGBoost algorithm. The method mainly comprises the following five steps of (1) receiving and preprocessing social media text data; (2) constructing a disaster word pre-training word vector table for converting social media text data into word vectors; (3) converting the social media text data preprocessed in the step (1) into a word vector with the dimension of d through the updated word vector table in the step (2), and performing information category classification and importance category classification on the social media text data by utilizing an XGBoost algorithm; (4) weighting the information classification result and the alarm classification resultof the social media text data to determine the importance of the contained text information. Based on social media text data, importance weighting functions are added, through dividing information categories and alarm categories of social media text data, the association degree between the information category and the alarm is established, classification is carried out by combining deep learningand an XGBoost algorithm, and the association between the information category and the alarm category is weighted to obtain a final social media text data information importance index. Experimental results show that the information importance classification effect of the social media text data is obviously improved.

Description

technical field [0001] The invention relates to a weighted classification method for disaster information importance of blog posts based on deep learning and XGBoost algorithm, and belongs to the technical field of Internet information classification. Background technique [0002] Social media has become an integral part of human life, such as Twitter, Weibo, etc. When natural disasters occur, such as natural disasters such as fires, earthquakes, flash floods, tsunamis, mudslides, etc., or emergencies such as shootings and robberies, if they are only broadcast through the media, the cycle of event rescue will be very slow. On February 28, 2019, China Internet Network Information Center (CNNIC) released the 43rd "Statistical Report on Internet Development in China" in Beijing. As of December 2018, the number of Internet users in my country reached 829 million, and the penetration rate reached 59.6%. At the end of the year, it increased by 3.8 percentage points, with 56.53 mil...

AI Technical Summary

Problems solved by technology

When natural disasters occur, such as natural disasters such as fires, earthquakes, mountain torrents, tsunamis, mudslides, etc., or emergencies such as shootings and robberies, the cycle of event rescue will be very slow if it is only broadcast through the media

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