Hadoop⁃based local timing link prediction algorithm across social networks

In order to improve the accuracy and stability of local time series link prediction for cross social network, a Hadoop based local time series link prediction algorithm is proposed. This algorithm selects six cross social network node similarity indicators, and designs a parallel computing model using the core component MapReduce of Hadoop, which can segment and process the massive parallel data in cross social network, and reduce the computational complexity. Based on this, the local time series link prediction algorithm based on MapReduce parallel operation model is used to obtain the point-to-point prediction score in the network by using the selected node similarity index, so as to realize the prediction of cross social network local temporal link. The experimental results show that the prediction accuracy of the proposed algorithm is high, it can maintain a stable prediction state, and has good comprehensive prediction performance. © 2022, Jilin University Press. All right reserved.