The invention discloses a multi-user sharing-oriented
multimedia network video recommendation method, which comprises the following steps: firstly, constructing multi-user characteristics by utilizing collected program information in a multi-user sharing environment, and constructing a leading user
label according to the similarity of the program characteristics and the continuity of user watching behaviors, so that separation of multi-user mixed logs is realized; performing periodic multi-user identification prediction of future sessions; secondly, building a user interest mining model based on a time-varying LinUCB
algorithm to learn interest changes of a user for each program theme, and enhancing the personalized ability and efficiency of a recommendation
system from three aspects of parallel calculation,
adaptive control of an exploration coefficient and incremental updating based on LSTM; and finally, establishing an article quality model based on a non-time-varying LinUCB
algorithm to further ensure the
program quality, and integrating the two algorithms into a final recommendation
system model by adopting a cross weighting strategy to form a final program recommendation
list. The novelty and accuracy of the recommendation result are ensured.