Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Adaptive on-line page importance computation
WWW '03 Proceedings of the 12th international conference on World Wide Web
The effect of the back button in a random walk: application for pagerank
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Updating pagerank with iterative aggregation
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
ACM Transactions on Internet Technology (TOIT)
TotalRank: ranking without damping
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
EventRank: a framework for ranking time-varying networks
Proceedings of the 3rd international workshop on Link discovery
Google's PageRank and Beyond: The Science of Search Engine Rankings
Google's PageRank and Beyond: The Science of Search Engine Rankings
Beyond streams and graphs: dynamic tensor analysis
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Link analysis for Web spam detection
ACM Transactions on the Web (TWEB)
Estimating PageRank on graph streams
Proceedings of the twenty-seventh ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Dynamical Systems and Non-Hermitian Iterative Eigensolvers
SIAM Journal on Numerical Analysis
Temporal Link Prediction Using Matrix and Tensor Factorizations
ACM Transactions on Knowledge Discovery from Data (TKDD)
Modeling dynamic behavior in large evolving graphs
Proceedings of the sixth ACM international conference on Web search and data mining
| Hi-index | 0.00 |
The importance of nodes in a network constantly fluctuates based on changes in the network structure as well as changes in external interest. We propose an evolving teleportation adaptation of the PageRank method to capture how changes in external interest influence the importance of a node. This framework seamlessly generalizes PageRank because the importance of a node will converge to the PageRank values if the external influence stops changing. We demonstrate the effectiveness of the evolving teleportation on the Wikipedia graph and the Twitter social network. The external interest is given by the number of hourly visitors to each page and the number of monthly tweets for each user.