Favorite tag mining method and device

Abstract

The invention discloses a user fond label mining method which comprises the following steps: acquiring a text and a corresponding audio and / or a face video; carrying out word segmentation on the text to obtain a word sequence; extracting an emotion main body and an emotion object from the word sequence; extracting a text feature vector of an emotional tendency of the emotion main body to the emotion object according to the text; extracting an audio feature vector of the emotional tendency of the emotion main body to the emotion object according to the audio, and / or extracting a video feature vector of the emotional tendency of the emotion main body to the emotion object according to the face video; judging the emotional tendency of the emotion main body to the emotion object by a trained emotional tendency judgment model according to the text feature vector, the audio feature vector and the video feature vector; generating a fond label of the emotion main body to the emotion object. According to the method, the user fond label capable of reflecting the real fond of a user more accurately can be mined. Furthermore, the invention further provides a user fond label mining device.

Description

technical field [0001] The invention relates to the field of data mining, in particular to a method and device for mining user preference tags. Background technique [0002] Common user tags are words, words, phrases or short sentences that can reflect user characteristics. The user preference tag is a user tag that can reflect user preferences or emotional tendencies. [0003] Existing Internet applications focus more on personalized services, recommending products and social information that are suitable for users, so as to improve the hit rate of information push and user stickiness. How to dig out the user's interest points, analyze the user's emotional tendency, and thus generate user preference tags are problems that many Internet applications hope to solve. [0004] Traditional technologies generally generate the user's preference tags through the keywords defined by other users in the social network for the user. However, due to the existence of personal subjective...

AI Technical Summary

Problems solved by technology

[0004] Traditional technologies generally generate the user's preference tags through the keywords defined by other users in the social network for the user. However, due to the existence of personal subjective factors, the generated user preference tags may not truly reflect the user's preferences and emotional tendencies.

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