Erratum: inverting a sum of matrices
SIAM Review
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Cumulated gain-based evaluation of IR techniques
ACM Transactions on Information Systems (TOIS)
Exploiting hierarchical domain structure to compute similarity
ACM Transactions on Information Systems (TOIS)
SimRank: a measure of structural-context similarity
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
CloseGraph: mining closed frequent graph patterns
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Fast discovery of connection subgraphs
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Automatic multimedia cross-modal correlation discovery
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Scaling link-based similarity search
WWW '05 Proceedings of the 14th international conference on World Wide Web
Matrix Analysis For Scientists And Engineers
Matrix Analysis For Scientists And Engineers
Substructure similarity search in graph databases
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
SimFusion: measuring similarity using unified relationship matrix
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Learning to rank using gradient descent
ICML '05 Proceedings of the 22nd international conference on Machine learning
Group formation in large social networks: membership, growth, and evolution
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Measuring and extracting proximity in networks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Beyond streams and graphs: dynamic tensor analysis
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Fast Random Walk with Restart and Its Applications
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Temporal Analysis of the Wikigraph
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
Evolutionary spectral clustering by incorporating temporal smoothness
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
A framework for community identification in dynamic social networks
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Accuracy estimate and optimization techniques for SimRank computation
Proceedings of the VLDB Endowment
Enhancing link-based similarity through the use of non-numerical labels and prior information
Proceedings of the Eighth Workshop on Mining and Learning with Graphs
Taming computational complexity: efficient and parallel simrank optimizations on undirected graphs
WAIM'10 Proceedings of the 11th international conference on Web-age information management
Recommendation of similar users, resources and social networks in a Social Internetworking Scenario
Information Sciences: an International Journal
CollabSeer: a search engine for collaboration discovery
Proceedings of the 11th annual international ACM/IEEE joint conference on Digital libraries
SFViz: interest-based friends exploration and recommendation in social networks
Proceedings of the 2011 Visual Information Communication - International Symposium
ASAP: towards accurate, stable and accelerative penetrating-rank estimation on large graphs
WAIM'11 Proceedings of the 12th international conference on Web-age information management
Finding information nebula over large networks
Proceedings of the 20th ACM international conference on Information and knowledge management
A space and time efficient algorithm for SimRank computation
World Wide Web
Discovering missing links in networks using vertex similarity measures
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Relevance search in heterogeneous networks
Proceedings of the 15th International Conference on Extending Database Technology
SympGraph: a framework for mining clinical notes through symptom relation graphs
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
SimFusion+: extending simfusion towards efficient estimation on large and dynamic networks
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
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 efficiency of estimating penetrating rank on large graphs
SSDBM'12 Proceedings of the 24th international conference on Scientific and Statistical Database Management
Targeted and scalable information dissemination in a distributed reputation mechanism
Proceedings of the seventh ACM workshop on Scalable trusted computing
E-rank: A Structural-Based Similarity Measure in Social Networks
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
IRWR: incremental random walk with restart
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
ASCOS: an asymmetric network structure COntext similarity measure
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Efficient simrank-based similarity join over large graphs
Proceedings of the VLDB Endowment
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Information networks are ubiquitous in many applications and analysis on such networks has attracted significant attention in the academic communities. One of the most important aspects of information network analysis is to measure similarity between nodes in a network. SimRank is a simple and influential measure of this kind, based on a solid theoretical "random surfer" model. Existing work computes SimRank similarity scores in an iterative mode. We argue that the iterative method can be infeasible and inefficient when, as in many real-world scenarios, the networks change dynamically and frequently. We envision non-iterative method to bridge the gap. It allows users not only to update the similarity scores incrementally, but also to derive similarity scores for an arbitrary subset of nodes. To enable the non-iterative computation, we propose to rewrite the SimRank equation into a non-iterative form by using the Kronecker product and vectorization operators. Based on this, we develop a family of novel approximate SimRank computation algorithms for static and dynamic information networks, and give their corresponding theoretical justification and analysis. The non-iterative method supports efficient processing of various node analysis including similarity tracking and centrality tracking on evolving information networks. The effectiveness and efficiency of our proposed methods are evaluated on synthetic and real data sets.