Weighted tree mining has become an important research topic in Data mining. There are several algorithms for mining Frequent Pattern trees. FP growth algorithm using FP tree has been considered for frequent pattern mining because of its enormous performance and development compared to the candidate generation model of Apriori. The purpose of our work is to provide a tree structure for incremental and interactive weighted pattern mining by only one database scan. It is applied to existing Compact pattern (CP) tree. CP tree dynamically achieves frequency-descending prefix tree structure with a single-pass by applying tree restructuring technique and considerably reducing the mining time. It is competent of using prior tree structures and acquires mining outcomes to decrease the computation by incredible amount. Performance analysis show that our tree structure is very efficient for incremental and interactive weighted pattern mining.