GENERALIZED MAXIMUM-DEGREE RANDOM WALK GRAPH SAMPLING ALGORITHM

摘要

A generalized maximum-degree random walk graph sampling algorithm, comprising: random walking on a graph to acquire a sample; and structuring an unbiased estimation according to the acquired sample. The algorithm can effectively balance a large deviation problem of an RW algorithm and a sample repetition problem of an MD algorithm, thus improving the overall efficiency of acquiring sample points from a network.