Assessing single-pair similarity over graphs by aggregating first-meeting probabilities

He, Jun; Liu, Hongyan; Yu, Jeffrey Xu; Li, Pei; He, Wei; Du, Xiaoyong

doi:10.1016/j.is.2013.12.008

Cited by 20 publications

(19 citation statements)

References 14 publications

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“…However, [3] delivers probabilistic results. To enhance search quality, Li et al [12] [6] has also employed position probability to reduce the time of [12] to O(k|E| 2 − |E|). All the bounds of these deterministic singlepair SimRank are still expensive.…”

Section: Single-pair Simrankmentioning

confidence: 99%

“…(6). Precisely, our method only requires 2k matrix-vector multiplications (k multiplications for W · u l−1 in Eq.…”

Section: A "Seed Germination" Iterative Model For Single-source Simrankmentioning

confidence: 99%

“…We refer to this phenomenon as "high iteration coupling". To the best of our knowledge, there are several pioneering works trying to break the "high iteration coupling" barrier, such as single-pair SimRank [3,6,12], and top-K single-source SimRank [4,9,10], but they still require excessive time and memory, or deliver probabilistic results. (see Related Work section for a detailed comparison).…”

Section: Introductionmentioning

confidence: 99%

“…First, it is a unified model, containing as special cases the existing all-pairs [13,16], single-source [4,10], and single-pair [6,12] SimRank, when (A, B) is taken to be (V, V ), (V, {j}), and ({i}, {j}), respectively, with queries i and j. Thus, it is applicable to any domains where all-pairs, single-source, and single-pair SimRank apply.…”

Section: Introductionmentioning

confidence: 99%

“…(1) Due to "high iteration coupling", it is difficult to break the holistic nature of the conventional iterative models for retrieving only partial-pairs SimRank in a self-contained style. (2) It is a grand challenge to improve both time and memory for partial-pairs SimRank without loss of accuracy, since even for computing a single-pair score, the prior works [6,12] have comparable complexities of all-pairs SimRank [13,16].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Efficient partial-pairs simrank search on large networks

McCann

2015

Proc. VLDB Endow.

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The assessment of node-to-node similarities based on graph topology arises in a myriad of applications, e.g., web search. SimRank is a notable measure of this type, with the intuition that "two nodes are similar if their in-neighbors are similar". While most existing work retrieving SimRank only considers all-pairs SimRank s(⋆, ⋆) and single-source SimRank s(⋆, j) (scores between every node and query j), there are appealing applications for partial-pairs SimRank, e.g., similarity join. Given two node subsets A and B in a graph, partial-pairs SimRank assessment aims to retrieve only {s(a, b)} ∀a∈A,∀b∈B . However, the best-known solution appears not self-contained since it hinges on the premise that the SimRank scores with node-pairs in an h-go cover set must be given beforehand. This paper focuses on efficient assessment of partial-pairs SimRank in a self-contained manner. (1) We devise a novel "seed germination" model that computes partial-pairs SimRank in O(k|E| min{|A|, |B|}) time and O(|E|+k|V |) memory for k iterations on a graph of |V | nodes and |E| edges.(2) We further eliminate unnecessary edge access to improve the time of partial-pairs SimRank to O(m min{|A|, |B|}), where m ≤ min{k|E|, ∆ 2k }, and ∆ is the maximum degree. (3) We show that our partial-pairs SimRank model also can handle the computations of all-pairs and single-source SimRanks. (4) We empirically verify that our algorithms are (a) 38x faster than the best-known competitors, and (b) memory-efficient, allowing scores to be assessed accurately on graphs with tens of millions of links.

show abstract

Section: Single-pair Simrankmentioning

confidence: 99%

“…(6). Precisely, our method only requires 2k matrix-vector multiplications (k multiplications for W · u l−1 in Eq.…”

Section: A "Seed Germination" Iterative Model For Single-source Simrankmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Efficient partial-pairs simrank search on large networks

McCann

2015

Proc. VLDB Endow.

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An Axiomatic Role Similarity Measure Based on Graph Topology

Iranmanesh

Haldar

et al. 2020

Communications in Computer and Information Science

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Simplifying Calculation of Graph Similarity Through Matrices

Ouyang

Chen

2016

Computer and Computing Technologies in Agriculture IX

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A method to simplify the calculation in the process of measuring graph similarity is proposed, where lots of redundant operations are avoided in order to quickly obtain the initial tickets matrix. In this proposal, the element value of the initial tickets matrix is assigned to 1 when it is positive in corresponding position of the paths matrix at the first time. The proposed method calculates the initial tickets matrix value based on the positive value in the paths matrix in a forward and backward way. An example is provided to illustrate that the method is feasible and effective.

show abstract

Assessing single-pair similarity over graphs by aggregating first-meeting probabilities

Cited by 20 publications

References 14 publications

Efficient partial-pairs simrank search on large networks

Efficient partial-pairs simrank search on large networks

An Axiomatic Role Similarity Measure Based on Graph Topology

Simplifying Calculation of Graph Similarity Through Matrices

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