On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
SALSA: the stochastic approach for link-structure analysis
ACM Transactions on Information Systems (TOIS)
Scaling personalized web search
WWW '03 Proceedings of the 12th international conference on World Wide Web
Group formation in large social networks: membership, growth, and evolution
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
The link-prediction problem for social networks
Journal of the American Society for Information Science and Technology
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Statistical properties of community structure in large social and information networks
Proceedings of the 17th international conference on World Wide Web
Estimating PageRank on graph streams
Proceedings of the twenty-seventh ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
ACM SIGIR Forum
TrustWalker: a random walk model for combining trust-based and item-based recommendation
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
What is Twitter, a social network or a news media?
Proceedings of the 19th international conference on World wide web
Space-optimal heavy hitters with strong error bounds
ACM Transactions on Database Systems (TODS)
Fast incremental and personalized PageRank
Proceedings of the VLDB Endowment
Fast personalized PageRank on MapReduce
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Random walk based entity ranking on graph for multidimensional recommendation
Proceedings of the fifth ACM conference on Recommender systems
Proceedings of the 3rd Annual ACM Web Science Conference
PowerGraph: distributed graph-parallel computation on natural graphs
OSDI'12 Proceedings of the 10th USENIX conference on Operating Systems Design and Implementation
GraphChi: large-scale graph computation on just a PC
OSDI'12 Proceedings of the 10th USENIX conference on Operating Systems Design and Implementation
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Random walks on graphs are a staple of many ranking and recommendation algorithms. Simulating random walks on a graph which fits in memory is trivial, but massive graphs pose a problem: the latency of following walks across network in a cluster or loading nodes from disk on-demand renders basic random walk simulation unbearably inefficient. In this work we propose DrunkardMob, a new algorithm for simulating hundreds of millions, or even billions, of random walks on massive graphs, on just a single PC or laptop. Instead of simulating one walk a time it processes millions of them in parallel, in a batch. Based on DrunkardMob and GraphChi we further propose a framework for easily expressing scalable algorithms based on graph walks.