Annealing attention rumor identification method and device based on user features
A technology of user characteristics and attention, applied in the field of social network security, can solve the problems of high labor demand and poor effect of early rumor identification, and achieve the effect of high computational efficiency, versatility and high accuracy
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[0075] The present invention mainly solves the above-mentioned problems that the traditional machine learning model has high labor requirements, the end-to-end method focuses on the text content features, the use of user features is too simple, and the early rumor identification effect is not good. In order to facilitate the detection of our inventive device process, now with figure 1 The model framework in , as an example to illustrate the process of rumor detection.
[0076] From figure 1 As can be seen in , the input user feature matrix data is learned and extracted through the annealed attention layer and the multi-layer perceptron. After extracting the time series attention weight matrix and the inter-feature attention weight matrix, they are combined with the original feature matrix information. Then throw another multi-layer perceptron to extract high-level representation vectors. Finally, the high-level representation vector is used as the input of the fully connect...
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