Acquiring public opinion and training word viscosity model

A word viscosity model training method, comprising:

• performing word segmentation on a text corpus to obtain a plurality of word pairs as a training sample, a word pair of the plurality of word pairs including a previous word and a latter word;
• training the word viscosity model based on the training sample to cause the word viscosity model to output, for each word pair of the plurality of word pairs, a probability that the previous word and the latter word of the word pair form a key phrase;
• and
• training the word viscosity model by gradient descent, until the word viscosity model meets a preset condition, wherein the preset condition includes a preset precision or a preset number of training.

A server, comprising:

• a processor;
• and
• a memory storing programs, the programs comprising instructions, which, when executed by the processor, cause the processor to carry out acts, including:
• receiving a public opinion acquisition request, the public opinion acquisition request including a public opinion keyword to be acquired;
• matching the public opinion keyword to be acquired with video data including a recognition result, wherein the recognition result is obtained by performing predefined content recognition on the video data, the predefined content recognition including text recognition and image recognition;
• and
• determining video data that matches with the public opinion keyword to be acquired as result video data.