The invention discloses a short video recommendation method and
system based on multi-
modal attention, and relates to the technical field of
big data pushing, and the recommendation steps are as follows: S1, obtaining short video watching historical data of a user, dividing a watching behavior into playing duration and a playing
completion rate based on the historical data and the watching time of the short video page, respectively endowing weights, and determining the playing duration and the playing
completion rate; converting the watching condition of the user into a quantized preference weighting value; and S2, respectively calculating preference emphasis values of different short videos in the historical data, and obtaining a preference threshold value for watching the short videos of the user based on
big data analysis. According to the method, active screening is carried out from the pre-generated recommended videos, the recommendation accuracy is further improved, the current specific requirements of the user are met, the videos with large differences are introduced as candidates to perfect the push
list, the correlation between the recommended videos and user preferences is ensured, the diversity of recommended contents is increased, and the user experience is improved. And aesthetic fatigue caused by the fact that the user sees too many similar videos is avoided, and user experience is improved.