The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Proceedings of the 11th international conference on World Wide Web
Extrapolation methods for accelerating PageRank computations
WWW '03 Proceedings of the 12th international conference on World Wide Web
Scaling personalized web search
WWW '03 Proceedings of the 12th international conference on World Wide Web
Proceedings of the 13th international conference on World Wide Web
To randomize or not to randomize: space optimal summaries for hyperlink analysis
Proceedings of the 15th international conference on World Wide Web
Beyond PageRank: machine learning for static ranking
Proceedings of the 15th international conference on World Wide Web
Estimating the global pagerank of web communities
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Optimizing web search using social annotations
Proceedings of the 16th international conference on World Wide Web
Link analysis using time series of web graphs
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
DirichletRank: Solving the zero-one gap problem of PageRank
ACM Transactions on Information Systems (TOIS)
Estimating PageRank on graph streams
Proceedings of the twenty-seventh ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
BrowseRank: letting web users vote for page importance
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Speeding up algorithms on compressed web graphs
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Mining rich session context to improve web search
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
A framework to compute page importance based on user behaviors
Information Retrieval
Parallelizing the computation of PageRank
WAW'07 Proceedings of the 5th international conference on Algorithms and models for the web-graph
SPIRE'10 Proceedings of the 17th international conference on String processing and information retrieval
Fast incremental and personalized PageRank
Proceedings of the VLDB Endowment
OOLAM: an opinion oriented link analysis model for influence persona discovery
Proceedings of the fourth ACM international conference on Web search and data mining
An Inner-Outer Iteration for Computing PageRank
SIAM Journal on Scientific Computing
Estimating PageRank on graph streams
Journal of the ACM (JACM)
Fast personalized PageRank on MapReduce
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Non-deterministic parallelism considered useful
HotOS'13 Proceedings of the 13th USENIX conference on Hot topics in operating systems
Index design and query processing for graph conductance search
The VLDB Journal — The International Journal on Very Large Data Bases
Page importance computation based on Markov processes
Information Retrieval
ClickRank: Learning Session-Context Models to Enrich Web Search Ranking
ACM Transactions on the Web (TWEB)
Overlapping clusters for distributed computation
Proceedings of the fifth ACM international conference on Web search and data mining
Efficient parallel computation of pagerank
ECIR'06 Proceedings of the 28th European conference on Advances in Information Retrieval
Efficient personalized pagerank with accuracy assurance
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Delta-SimRank computing on MapReduce
Proceedings of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications
On the embeddability of random walk distances
Proceedings of the VLDB Endowment
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In this note we consider a simple reformulation of the traditional power iteration algorithm for computing the stationary distribution of a Markov chain. Rather than communicate their current probability values to their neighbors at each step, nodes instead communicate only changes in probability value. This reformulation enables a large degree of flexibility in the manner in which nodes update their values, leading to an array of optimizations and features, including faster convergence, efficient incremental updating, and a robust distributed implementation.While the spirit of many of these optimizations appear in previous literature, we observe several cases where this unification simplifies previous work, removing technical complications and extending their range of applicability. We implement and measure the performance of several optimizations on a sizable (34M node) web subgraph, seeing significant composite performance gains, especially for the case of incremental recomputation after changes to the web graph.