Graph Mining Algorithms. The rst is the design of scal-able graph mining algorithms in MapReduce. Includes various graph mining algorithms including PageR-ank 39 Random Walk with Restart RWR 40 diame-terradius estimation 27 connected components 21 and eigensolver 22.
I have been selected as an Amazon Graduate Research Fellow. The algorithm requires only a small fraction of the input data instances to be labeled and works by iteratively propagating labels along the edges of a similarity graph. This paper has two focuses.
November 30 2020 - Our work Autonomous Graph Mining Algorithm Search with Best SpeedAccuracy Trade-off.
28 share. For example in order to test the next-generation Internet protocol we would like to simulate it on a. A path can be formed by more than two edges. Processing graphs with hundreds of billions of edges is only possible via developing distributed algorithms under distributed graph mining frameworks such as MapReduce Pregel Gigraph and alike.
