The invention discloses a digital
media content recommendation optimization method based on behavior analysis, and particularly relates to the field of digital media recommendation, comprising the following steps: step S1, collecting interactive behavior data of a user and digital
media content, including explicit behaviors and implicit behaviors; s2, the user requests to open a camera of the user during browsing, the user collects the face of the user through the camera after agreement, and facial behavior data is obtained after the facial data of the user is analyzed and transmitted to the interactive behavior data; s3, under the condition that the
data point set is obtained, the original frequency of the
data point set is analyzed, and the dynamic frequency of the
data point set is calculated; and S4, constructing a short-term interest and long-term interest fused dynamic model. The subconscious emotional tendency of the user can be captured, the problem of poor recommendation timeliness is effectively solved, interest modeling is closer to the real preference of the user, and the situation that a recommendation
system deviates from the core interest of the user due to useless data is avoided.