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Weighted MUSE for Frequent Sub-Graph Pattern Finding in Uncertain DBLP Data
2011 International Conference on Internet Technology and Applications
Studies shows that finding frequent sub-graphs in uncertain graphs database is an NP complete problem. Finding the frequency at which these sub-graphs occur in uncertain graph database is also computationally expensive. This paper focus on investigation of mining frequent sub-graph patterns in DBLP uncertain graph data using an approximation based method. The frequent sub-graph pattern mining problem is formalized by using the expected support measure. Here n approximate mining algorithm baseddoi:10.1109/itap.2011.6006415 fatcat:kglhmiqdcrabndrvuhgu5n2oha