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A query suggestion algorithm is presented based on query logs mining and semantic. First construct a weighted Query-URL bipartite graph from query log data. Then compute the semantic similarity of queries by distance of queries nodes and synonymy similarity to extracting semantic related queries based on graph path. Experiments show that the algorithm is more effective than substring extending algorithm and log mining algorithm in recall and precision.