AILabel: A Fast Interval Labeling Approach for Reachability Query on Very Large Graphs

Author(s):  
Feng Shuo ◽  
Xie Ning ◽  
Shen de-Rong ◽  
Li Nuo ◽  
Kou Yue ◽  
...  
Author(s):  
Renato Vizuete ◽  
Federica Garin ◽  
Paolo Frasca

2021 ◽  
Vol 15 (4) ◽  
Author(s):  
Yun Peng ◽  
Xin Lin ◽  
Byron Choi ◽  
Bingsheng He

2021 ◽  
Vol 15 (6) ◽  
pp. 1-27
Author(s):  
Marco Bressan ◽  
Stefano Leucci ◽  
Alessandro Panconesi

We address the problem of computing the distribution of induced connected subgraphs, aka graphlets or motifs , in large graphs. The current state-of-the-art algorithms estimate the motif counts via uniform sampling by leveraging the color coding technique by Alon, Yuster, and Zwick. In this work, we extend the applicability of this approach by introducing a set of algorithmic optimizations and techniques that reduce the running time and space usage of color coding and improve the accuracy of the counts. To this end, we first show how to optimize color coding to efficiently build a compact table of a representative subsample of all graphlets in the input graph. For 8-node motifs, we can build such a table in one hour for a graph with 65M nodes and 1.8B edges, which is times larger than the state of the art. We then introduce a novel adaptive sampling scheme that breaks the “additive error barrier” of uniform sampling, guaranteeing multiplicative approximations instead of just additive ones. This allows us to count not only the most frequent motifs, but also extremely rare ones. For instance, on one graph we accurately count nearly 10.000 distinct 8-node motifs whose relative frequency is so small that uniform sampling would literally take centuries to find them. Our results show that color coding is still the most promising approach to scalable motif counting.


2021 ◽  
Vol 2 (3) ◽  
pp. 100677
Author(s):  
Emile Alghoul ◽  
Jihane Basbous ◽  
Angelos Constantinou

2021 ◽  
Vol 15 (5) ◽  
pp. 1-52
Author(s):  
Lorenzo De Stefani ◽  
Erisa Terolli ◽  
Eli Upfal

We introduce Tiered Sampling , a novel technique for estimating the count of sparse motifs in massive graphs whose edges are observed in a stream. Our technique requires only a single pass on the data and uses a memory of fixed size M , which can be magnitudes smaller than the number of edges. Our methods address the challenging task of counting sparse motifs—sub-graph patterns—that have a low probability of appearing in a sample of M edges in the graph, which is the maximum amount of data available to the algorithms in each step. To obtain an unbiased and low variance estimate of the count, we partition the available memory into tiers (layers) of reservoir samples. While the base layer is a standard reservoir sample of edges, other layers are reservoir samples of sub-structures of the desired motif. By storing more frequent sub-structures of the motif, we increase the probability of detecting an occurrence of the sparse motif we are counting, thus decreasing the variance and error of the estimate. While we focus on the designing and analysis of algorithms for counting 4-cliques, we present a method which allows generalizing Tiered Sampling to obtain high-quality estimates for the number of occurrence of any sub-graph of interest, while reducing the analysis effort due to specific properties of the pattern of interest. We present a complete analytical analysis and extensive experimental evaluation of our proposed method using both synthetic and real-world data. Our results demonstrate the advantage of our method in obtaining high-quality approximations for the number of 4 and 5-cliques for large graphs using a very limited amount of memory, significantly outperforming the single edge sample approach for counting sparse motifs in large scale graphs.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Michał Ławniczak ◽  
Adam Sawicki ◽  
Małgorzata Białous ◽  
Leszek Sirko

AbstractWe identify and investigate isoscattering strings of concatenating quantum graphs possessing n units and 2n infinite external leads. We give an insight into the principles of designing large graphs and networks for which the isoscattering properties are preserved for $$n \rightarrow \infty $$ n → ∞ . The theoretical predictions are confirmed experimentally using $$n=2$$ n = 2 units, four-leads microwave networks. In an experimental and mathematical approach our work goes beyond prior results by demonstrating that using a trace function one can address the unsettled until now problem of whether scattering properties of open complex graphs and networks with many external leads are uniquely connected to their shapes. The application of the trace function reduces the number of required entries to the $$2n \times 2n $$ 2 n × 2 n scattering matrices $${\hat{S}}$$ S ^ of the systems to 2n diagonal elements, while the old measures of isoscattering require all $$(2n)^2$$ ( 2 n ) 2 entries. The studied problem generalizes a famous question of Mark Kac “Can one hear the shape of a drum?”, originally posed in the case of isospectral dissipationless systems, to the case of infinite strings of open graphs and networks.


2005 ◽  
Vol 11 (4) ◽  
pp. 457-468 ◽  
Author(s):  
E.R. Gansner ◽  
Y. Koren ◽  
S.C. North
Keyword(s):  

2015 ◽  
Vol 8 (3) ◽  
pp. 183-202 ◽  
Author(s):  
Danai Koutra ◽  
U Kang ◽  
Jilles Vreeken ◽  
Christos Faloutsos
Keyword(s):  

2013 ◽  
Vol 79 (18) ◽  
pp. 5670-5681 ◽  
Author(s):  
Philipp Adler ◽  
Christoph Josef Bolten ◽  
Katrin Dohnt ◽  
Carl Erik Hansen ◽  
Christoph Wittmann

ABSTRACTIn the present work, simulated cocoa fermentation was investigated at the level of metabolic pathway fluxes (fluxome) of lactic acid bacteria (LAB), which are typically found in the microbial consortium known to convert nutrients from the cocoa pulp into organic acids. A comprehensive13C labeling approach allowed to quantify carbon fluxes during simulated cocoa fermentation by (i) parallel13C studies with [13C6]glucose, [1,2-13C2]glucose, and [13C6]fructose, respectively, (ii) gas chromatography-mass spectrometry (GC/MS) analysis of secreted acetate and lactate, (iii) stoichiometric profiling, and (iv) isotopomer modeling for flux calculation. The study of several strains ofL. fermentumandL. plantarumrevealed major differences in their fluxes. TheL. fermentumstrains channeled only a small amount (4 to 6%) of fructose into central metabolism, i.e., the phosphoketolase pathway, whereas onlyL. fermentumNCC 575 used fructose to form mannitol. In contrast,L. plantarumstrains exhibited a high glycolytic flux. All strains differed in acetate flux, which originated from fractions of citrate (25 to 80%) and corresponding amounts of glucose and fructose. Subsequent, metafluxome studies with consortia of differentL. fermentumandL. plantarumstrains indicated a dominant (96%) contribution ofL. fermentumNCC 575 to the overall flux in the microbial community, a scenario that was not observed for the other strains. This highlights the idea that individual LAB strains vary in their metabolic contribution to the overall fermentation process and opens up new routes toward streamlined starter cultures.L. fermentumNCC 575 might be one candidate due to its superior performance in flux activity.


PLoS ONE ◽  
2014 ◽  
Vol 9 (11) ◽  
pp. e112596 ◽  
Author(s):  
Luciano Antonio Reolon ◽  
Carolina Lumertz Martello ◽  
Irene Silveira Schrank ◽  
Henrique Bunselmeyer Ferreira

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