Abstract: Mining association rules is one of the primary methods used in telecommunication alarm correlation analysis. The efficiency of the algorithms plays an important role in tackling with large datasets. A highly efficient algorithm of weighted association rules mining in telecommunication networks based on weighted frequent pattern tree is proposed. The performance test of the algorithm indicates that compared with other algorithms of weighted association rules mining, this one needs less memory and has higher temporal efficiency, which is significant for the network fault diagnosis and localization.