Research on big data personalised recommendation model based on deep reinforcement learning

In order to mine the user's preference and interest from the user's historical behaviour in the big data to make a personalised recommendation, a DRR model is constructed based on deep reinforcement learning, and the performance of the DRR model is analysed through experiments. The results showed that the DRR model had a higher effect than other comparable models in the offline experimental evaluation, and the DRR-att value was the highest, reaching 0.9025. In the online simulation experiment, the average DRR-att value was the highest reward rate, reaching 0.7466. In general, the DRR model had better analysis ability and strong dynamic modelling ability and was good at using long-term rewards for decision making. In the parameter analysis experiment, the T value reached ten points. At the same time, the user state expression module can improve the accuracy of the DRR model and is effective in actual user personalised recommendations.