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A space and time efficient algorithm for SimRank computation

Weiren Yu, Wenjie Zhang, Xuemin Lin, Qing Zhang, Jiajin Le
2010 World wide web (Bussum)  
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.  ...  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  ...  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

A Space and Time Efficient Algorithm for SimRank Computation

Weiren Yu, Xuemin Lin, Jiajin Le
2010 2010 12th International Asia-Pacific Web Conference  
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.  ...  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  ...  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

Scalable similarity search for SimRank

Mitsuru Kusumoto, Takanori Maehara, Ken-ichi Kawarabayashi
2014 Proceedings of the 2014 ACM SIGMOD international conference on Management of data - SIGMOD '14  
Therefore, in order to compute SimRank scores for a query vertex u for our similarity search problem, we only need to look at very "local" area. 4.  ...  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

Zhipeng Zhang, Yingxia Shao, Bin Cui, Ce Zhang
2017 Proceedings of the VLDB Endowment  
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  ...  This has led to many algorithms that efficiently calculate or approximate SimRank being proposed by researchers.  ...  NI-Sim computes a single-pair SimRank query in O(r 4 ) time with O(n 2 r 2 +r 4 ) space.  ... 
doi:10.14778/3055540.3055552 fatcat:qb6alvxakfcd5dtyxqzrvpc6sm

SLING

Boyu Tian, Xiaokui Xiao
2016 Proceedings of the 2016 International Conference on Management of Data - SIGMOD '16  
Scalable SimRank computation has been the subject of extensive research for more than a decade, and yet, none of the existing solutions can efficiently derive SimRank scores on large graphs with provable  ...  This paper presents SLING, an efficient index structure for Sim-Rank computation.  ...  A. McCann. High quality graph-based similarity search. In SIGIR, pages 83-92, 2015. [34] W. Yu, W. Zhang, X. Lin, Q. Zhang, and J. Le. A space and time efficient algorithm for simrank computation.  ... 
doi:10.1145/2882903.2915243 dblp:conf/sigmod/TianX16 fatcat:knawxogzabderamhycpxo7hvkm

Delta-SimRank computing on MapReduce

Liangliang Cao, Brian Cho, Hyun Duk Kim, Zhen Li, Min-Hsuan Tsai, Indranil Gupta
2012 Proceedings of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining Algorithms, Systems, Programming Models and Applications - BigMine '12  
This paper considers the problem of computing SimRank efficiently in a distributed system while handling dynamic networks which grow with time.  ...  Most existing efforts to accelerate SimRank computation work only for static graphs and on single machines.  ...  Given a graph with N nodes and D edges, the time complexity of computing PageRank is O(D) and a space complexity is O(N ).  ... 
doi:10.1145/2351316.2351321 dblp:conf/kdd/CaoCKLTG12 fatcat:lffnokhzdvbtpmuve2mya6wbzi

SLING: A Near-Optimal Index Structure for SimRank [article]

Boyu Tian, Xiaokui Xiao
2016 arXiv   pre-print
This paper presents SLING, an efficient index structure for SimRank computation.  ...  Scalable SimRank computation has been the subject of extensive research for more than a decade, and yet, none of the existing solutions can efficiently derive SimRank scores on large graphs with provable  ...  Figure 8 : 8 An adversarial case for the linearization method. [33] W. Yu, W. Zhang, X. Lin, Q. Zhang, and J. Le. A space and time efficient algorithm for simrank computation.  ... 
arXiv:1604.04185v1 fatcat:npytvjpmczgvvomlhqwawzgfni

Efficient SimRank Computation via Linearization [article]

Takanori Maehara, Mitsuru Kusumoto, Ken-ichi Kawarabayashi
2014 arXiv   pre-print
While there are many algorithms proposed for computing SimRank, their computational costs are very high.  ...  In this paper, we propose a new computational technique, "SimRank linearization," for computing SimRank, which converts the SimRank problem to a linear equation problem.  ...  This algorithm computes all-pairs SimRank in O(nm) time and O(n 2 ) space.  ... 
arXiv:1411.7228v1 fatcat:z3bf2ekfkvfjrbxddq5gorrtk4

Dynamical SimRank search on time-varying networks

Weiren Yu, Xuemin Lin, Wenjie Zhang, Julie A. McCann
2017 The VLDB journal  
Many real graphs are large, and links are constantly subject to minor changes. In this article, we study the efficient dynamical computation of all-pairs SimRanks on time-varying graphs.  ...  As a result, all pairs of SimRanks are updated approximately, yielding O(r 4 n 2 ) time and O(r 2 n 2 ) memory in a graph with n nodes, where r is the B Weiren Yu  ...  The original batch algorithm in [9] (resp. [13] ) serves as the exact solution to obtain SimRank results for LTSF (resp. Inc-SR-All-P).  ... 
doi:10.1007/s00778-017-0488-z fatcat:a3xzy2cfzne2ra3gc7pn3g7wwq

Dynamical SimRank Search on Time-Varying Networks [article]

Weiren Yu, Xuemin Lin, Wenjie Zhang, Julie A. McCann
2017 arXiv   pre-print
In this article, we study the efficient dynamical computation of all-pairs SimRanks on time-varying graphs. Li et al.'  ...  This provides an incremental method requiring O(Kn^2) time and O(n^2) memory in the worst case to update all pairs of similarities for K iterations. (2) To speed up the computation further, we propose  ...  Algorithm 4 presents an efficient batch updates algorithm, Inc-bSR, for dynamical SimRank computation.  ... 
arXiv:1711.00121v1 fatcat:mphnp4ismbh4np24wz4zknnrrm

An efficient similarity search framework for SimRank over large dynamic graphs

Yingxia Shao, Bin Cui, Lei Chen, Mingming Liu, Xing Xie
2015 Proceedings of the VLDB Endowment  
Nowadays, graphs in the real world become much larger and more dynamic. The existing solutions for similarity search are expensive in terms of time and space cost.  ...  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  ...  For example, the solution of computing SimRank scores in [21] costs O(N 3 ) time and O(N 2 ) space. As a consequence, the straightforward approach cannot process large graphs.  ... 
doi:10.14778/2757807.2757809 fatcat:kxltrqvpgramfbznz7b3ahcodm

Sig-SR

Weiren Yu, Julie A. McCann
2014 Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval - SIGIR '14  
plus a scaled identity matrix. (2) By virtue of this, an efficient algorithm over singular graphs, Sig-SR, is proposed for calculating all-pairs SimRank in O(r(n 2 + Kr 2 )) time for K iterations.  ...  In contrast, the only known matrix-based algorithm that supports singular graphs [2] needs O(r 4 n 2 ) time.  ...  Thus, it is imperative to provide a treatment for SimMat, by devising an efficient algorithm that supports SimRank computations on singular graphs.  ... 
doi:10.1145/2600428.2609459 dblp:conf/sigir/YuM14 fatcat:d4sgjqtuy5aijj7o3tzznfnaey

Taming Computational Complexity: Efficient and Parallel SimRank Optimizations on Undirected Graphs [chapter]

Weiren Yu, Xuemin Lin, Jiajin Le
2010 Lecture Notes in Computer Science  
To efficiently handle large-scale computations, we also propose a parallel implementation of the SimRank algorithm on multiple processors.  ...  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.  ...  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

CoSimRank: A Flexible and Efficient Graph-Theoretic Similarity Measure

Sascha Rothe, Hinrich Schütze
2014 Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)  
We present equivalent formalizations that show CoSimRank's close relationship to Personalized Page-Rank and SimRank and also show how we can take advantage of fast matrix multiplication algorithms to compute  ...  We present CoSimRank, a graph-theoretic similarity measure that is efficient because it can compute a single node similarity without having to compute the similarities of the entire graph.  ...  We showed that CoSimRank is superior to SimRank in time and space complexity; and we demonstrated that CoSimRank performs better than PPR+cos on two similarity computation tasks. Acknowledgments.  ... 
doi:10.3115/v1/p14-1131 dblp:conf/acl/RotheS14 fatcat:xrujeahimfefba5lg2q5nktcvi

ASCOS

Hung-Hsuan Chen, C. Lee Giles
2013 Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining - ASONAM '13  
When the target network is sparse, the run time and the required computing space of these variations are smaller than computing SimRank and ASCOS directly.  ...  To make ASCOS tractable in both computation time and memory usage, we propose two variations of ASCOS: a low rank approximation based approach and an iterative solver Gauss-Seidel for linear equations.  ...  Acknowledgments We gratefully acknowledge partial support by the National Science Foundation and Dow Chemical.  ... 
doi:10.1145/2492517.2492539 dblp:conf/asunam/ChenG13 fatcat:b5olwqzglncj3iivbmq2jvt7ui
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