Music Recommendation Index Evaluation Based on Logistic Distribution Fitting Transition Probability Function

Abstract This paper proposes a simulation algorithm of transition probability function based on logistic distribution. method mainly models popularity and state functions by acquiring consumers' music preferences likes. Through this mathematical model, obtains the best results that are more in line with consumer preference. conducts experiment collecting Netease cloud data. Finally, through comparison empirical data, it is further demonstrated model has particular practical value.