Estimating PageRank on Graph Streams
- Atish Das Sarma ,
- Rina Panigrahy ,
- Sreenivas Gollapudi
Proceedings of the Twenty-Seventh ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems |
Published by Association for Computing Machinery, Inc.
(Best Paper Award)
This study focuses on computations on large graphs (e.g., the web-graph) where the edges of the graph are presented as a stream. The objective in the streaming model is to use small amount of memory (preferably sub-linear in the number of nodes n) and a few passes. In the streaming model, we show how to perform several graph computations including estimating the probability distribution after a random walk of length l, mixing time, and the conductance.
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