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Micro-blog user community discovery using generalized SimRank edge weighting method
2018
PLoS ONE
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A novel edge weighting method which balances local and global weighting PLOS ONE | https://doi. ...
This paper proposes a novel edge weighting method, which balances both local and global weighting based on the idea of shared neighbor ranging between users and the interpersonal significance of the social ...
The GN and fast Newman algorithms, the SimRank edge weighting algorithm, and the concept of modularity are discussed. ...
doi:10.1371/journal.pone.0196447
pmid:29734358
pmcid:PMC5937763
fatcat:sy2ej66ehzfn5mzp7de3geg3na
A Space and Time Efficient Algorithm for SimRank Computation
2010
2010 12th International Asia-Pacific Web Conference
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In this paper, we propose novel optimization techniques such that each iteration takes O (min {n · m, n r }) time and O (n + m) space, where m is the number of edges in a web-graph model and r ≤ log 2 ...
SimRank has become an important similarity measure to rank web documents based on a graph model on hyperlinks. The existing approaches for conducting SimRank computation adopt an iteration paradigm. ...
Real-life datasets For real datasets, we verified our algorithms over (1) ten-year (from 1998 to 2007) DBLP dataset, and (2) three English Wikipedia category graphs. ...
doi:10.1109/apweb.2010.42
dblp:conf/apweb/YuLL10
fatcat:ktzfyq5jv5ecdgrpn4zfczqoue
Fast, memory-efficient low-rank approximation of SimRank
2016
Journal of Complex Networks
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SimRank is a well-known similarity measure between graph vertices. In this paper novel low-rank approximation of SimRank is proposed. ...
Sadovsky and D.A. Podlesnykh. ...
The result for original iterative simrank algorithm gives the following SimRank matrix: As we can see even for such small and simple example the discrepancy not negligible: the S 4,4 and S 5,5 significantly ...
doi:10.1093/comnet/cnw008
fatcat:5vqgqpritjh3hpwh6zmb2pvjpq
Taming Computational Complexity: Efficient and Parallel SimRank Optimizations on Undirected Graphs
[chapter]
2010
Lecture Notes in Computer Science
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We first present a novel algorithm to estimate the SimRank between vertices in O n 3 + K · n 2 time, where n is the number of vertices, and K is the number of iterations. ...
To efficiently handle large-scale computations, we also propose a parallel implementation of the SimRank algorithm on multiple processors. ...
The second author was supported by three ARC DPs (DP0666428, DP0881035, and DP0987557) and a Google research award. ...
doi:10.1007/978-3-642-14246-8_29
fatcat:sgjuysmvurgbhpqsaju5pbsvqa
A space and time efficient algorithm for SimRank computation
2010
World wide web (Bussum)
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In this paper, we propose novel optimization techniques such that each iteration takes O (min {n · m, n r }) time and O (n + m) space, where m is the number of edges in a web-graph model and r ≤ log 2 ...
SimRank has become an important similarity measure to rank web documents based on a graph model on hyperlinks. The existing approaches for conducting SimRank computation adopt an iteration paradigm. ...
Real-life datasets For real datasets, we verified our algorithms over (1) ten-year (from 1998 to 2007) DBLP dataset, and (2) three English Wikipedia category graphs. ...
doi:10.1007/s11280-010-0100-6
fatcat:pirquc2zkfbbbjpkze6yj4ltke
Fast, memory efficient low-rank approximation of SimRank
[article]
2014
arXiv
pre-print
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SimRank is a well-known similarity measure between graph vertices. In this paper novel low-rank approximation of SimRank is proposed. ...
Sadovsky and D.A. Podlesnykh. ...
The result for original iterative simrank algorithm gives the following SimRank matrix: As we can see even for such small and simple example the discrepancy not negligible: the S 4,4 and S 5,5 significantly ...
arXiv:1410.0717v1
fatcat:omf53r64pjgl5bjtga5yqsu24m
An efficient similarity search framework for SimRank over large dynamic graphs
2015
Proceedings of the VLDB Endowment
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In this paper, we propose a novel two-stage random-walk sampling framework (TSF) for SimRank-based similarity search (e.g., top-k search). ...
In the preprocessing stage, TSF samples a set of one-way graphs to index raw random walks in a novel manner within O(N Rg) time and space, where N is the number of vertices and Rg is the number of one-way ...
Fogaras and Rácz [9] proposed the first random-walk based algorithm for fast SimRank search. ...
doi:10.14778/2757807.2757809
fatcat:kxltrqvpgramfbznz7b3ahcodm
Fast incremental SimRank on link-evolving graphs
2014
2014 IEEE 30th International Conference on Data Engineering
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In this paper, we propose a novel fast incremental paradigm. (1) We characterize the SimRank update matrix ∆S, in response to every link update, via a rank-one Sylvester matrix equation. ...
Our empirical evaluations verify that our algorithm (a) outperforms the best known link-update algorithm [1], and (b) runs much faster than its batch counterpart when link updates are small. ...
Inspired by this, we propose a novel fast (exact 8 ) algorithm for incrementally computing SimRank on link-evolving graphs. ...
doi:10.1109/icde.2014.6816660
dblp:conf/icde/YuLZ14
fatcat:65bru73y7ndbti42youfmoavma
Fast computation of SimRank for static and dynamic information networks
2010
Proceedings of the 13th International Conference on Extending Database Technology - EDBT '10
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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. ...
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 have proposed a novel non-iterative framework for SimRank computation. ...
doi:10.1145/1739041.1739098
dblp:conf/edbt/LiHHJSYW10
fatcat:5v7j5k5cizbdxcg2ucebacutre
Semisupervised Clustering for Networks Based on Fast Affinity Propagation
2013
Mathematical Problems in Engineering
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We propose a semisupervised clustering algorithm for networks based on fast affinity propagation (SCAN-FAP), which is essentially a kind of similarity metric learning method. ...
Then, taking the constraint similarities as input, we propose a fast affinity propagation algorithm which keeps the advantages of the original affinity propagation algorithm while increasing the time efficiency ...
For the similarities adjustments, we define a novel measure integrating the pairwise constraints and the basic SimRank similarities. ...
doi:10.1155/2013/385265
fatcat:65fto7rn4bdkxkpqqfhcq3mxoe
Scalable similarity search for SimRank
2014
Proceedings of the 2014 ACM SIGMOD international conference on Management of data - SIGMOD '14
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This allows us to formulate a problem that we can propose a very fast algorithm. 2. ...
We propose a very fast and scalable algorithm for this similarity search problem. Our method consists of the following ingredients: 1. We first introduce a "linear" recursive formula for Sim-Rank. ...
We first establish a new framework of computing Sim-Rank, which introduces a "linear" recursive formula for SimRank. ...
doi:10.1145/2588555.2610526
dblp:conf/sigmod/KusumotoMK14
fatcat:kv2gs4225jd7pcl4kjrzb6ie2m
An experimental evaluation of simrank-based similarity search algorithms
2017
Proceedings of the VLDB Endowment
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We first introduce a taxonomy for different algorithms that calculate SimRank and classify each algorithm into one of the following three classes, namely, iterative-, non-iterative-, and random walk-based ...
Given a graph, SimRank is one of the most popular measures of the similarity between two vertices. ...
This is because the accuracy loss of TopSim-based algorithms comes from the limited length of the random walks and SimRank converges fast in a short distance. ...
doi:10.14778/3055540.3055552
fatcat:qb6alvxakfcd5dtyxqzrvpc6sm
Co-Simmate: Quick Retrieving All Pairwise Co-Simrank Scores
2015
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)
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Co-Simrank is a useful Simrank-like measure of similarity based on graph structure. ...
Moreover, we show the optimality of Co-Simmate among other hop-(u k ) variations, and integrate it with a matrix decomposition based method on singular graphs to attain higher efficiency. ...
Co-Simmate (9) can also be combined with other factorisation methods, e.g., Sig-SR, a Co-Simrank algorithm proposed by (Yu and McCann, 2014) , to speed up all pairs of Co-Simrank computation from O( ...
doi:10.3115/v1/p15-2054
dblp:conf/acl/YuM15
fatcat:l4grmw2abfb5leajbcrjnuyof4
A Scalable Randomized Method to Compute Link-Based Similarity Rank on the Web Graph
[chapter]
2004
Lecture Notes in Computer Science
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The algorithms were tested on a set of ten million pages, but parallelization techniques make it possible to compute the SimRank scores even for the entire web with over 4 billion pages. ...
We introduce scalable algorithms computing SimRank scores, which express the contextual similarities of pages based on the hyperlink structure. ...
Conclusion We showed a method for computing the SimRank similarity scores for web pages. ...
doi:10.1007/978-3-540-30192-9_55
fatcat:2xtr5dixizexpef7qchuy4mgn4
SimRank Computation on Uncertain Graphs
[article]
2015
arXiv
pre-print
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SimRank is a similarity measure between vertices in a graph, which has become a fundamental technique in graph analytics. ...
The extensive experiments and case studies verify the effectiveness of our SimRank measure and the efficiency of our SimRank computation algorithms. ...
Later, [24] improved the running time to O(nd|V | 2 ) by sum memorization, and [40] speeded up the algorithm by fast matrix multiplication. ...
arXiv:1512.02714v1
fatcat:vzn43t5mfjbufoxdt5qbbzpsue
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