Mining weighted frequent patterns using local graph linking information

Data mining for traversal patterns has been found useful in several applications.However,traditional model of tra-versal patterns mining only considered unweighted traversals.This paper proposed a transformable model of EWDG(edge-weighted directed graph) and VWDG(vertex-weighted directed graph)to resolve the problem of weighted traversal patterns mining.Based on the model,developed a new algorithm,called LGTWFPMiner(local graph traversals-based weighted frequent patterns miner),and its local estimation of support/weight-bound to discover weighted frequent patterns from the traversals on graph with a level property.Experimental results of synthetic data show the algorithm is effective to resolve the problem of mi-ning weighted frequent patterns based on graph traversals.