Abstract: The paper presents an algorithm called WHOT (Weighted Hypergraphbased Outlier Test), which is based on weighted association rule mining algorithm and hypergraph partitioning algorithm. The association rule mining algorithm was redesigned. Hypergraph was constructed by mining significant association rules in data set. Cluster set was obtained by using the hypergraph partitioning algorithm. After that we defined the measures to judge whether a vertex in hypergraph or a record in dataset is an outlier.

Key words: data mining, outlier, hypergraph, weight