Graph stream algorithms: a survey
A McGregor - ACM SIGMOD Record, 2014 - dl.acm.org
Over the last decade, there has been considerable interest in designing algorithms for
processing massive graphs in the data stream model. The original motivation was two-fold …
processing massive graphs in the data stream model. The original motivation was two-fold …
Counting and sampling triangles from a graph stream
This paper presents a new space-efficient algorithm for counting and sampling triangles--
and more generally, constant-sized cliques--in a massive graph whose edges arrive as a …
and more generally, constant-sized cliques--in a massive graph whose edges arrive as a …
Triest: Counting local and global triangles in fully dynamic streams with fixed memory size
“Ogni lassada xe persa.” 1--Proverb from Trieste, Italy. We present trièst, a suite of one-pass
streaming algorithms to compute unbiased, low-variance, high-quality approximations of the …
streaming algorithms to compute unbiased, low-variance, high-quality approximations of the …
{Communication-Efficient} triangle counting under local differential privacy
Triangle counting in networks under LDP (Local Differential Privacy) is a fundamental task
for analyzing connection patterns or calculating a clustering coefficient while strongly …
for analyzing connection patterns or calculating a clustering coefficient while strongly …
Better algorithms for counting triangles in data streams
A McGregor, S Vorotnikova, HT Vu - … of the 35th ACM SIGMOD-SIGACT …, 2016 - dl.acm.org
We present space-efficient data stream algorithms for approximating the number of triangles
in a graph up to a factor 1+ ε. While it can be shown that determining whether a graph is …
in a graph up to a factor 1+ ε. While it can be shown that determining whether a graph is …
Differentially private triangle and 4-cycle counting in the shuffle model
Subgraph counting is fundamental for analyzing connection patterns or clustering
tendencies in graph data. Recent studies have applied LDP (Local Differential Privacy) to …
tendencies in graph data. Recent studies have applied LDP (Local Differential Privacy) to …
Counting arbitrary subgraphs in data streams
We study the subgraph counting problem in data streams. We provide the first non-trivial
estimator for approximately counting the number of occurrences of an arbitrary subgraph H …
estimator for approximately counting the number of occurrences of an arbitrary subgraph H …
An in-depth study of continuous subgraph matching
Continuous subgraph matching (CSM) algorithms find the occurrences of a given pattern on
a stream of data graphs online. A number of incremental CSM algorithms have been …
a stream of data graphs online. A number of incremental CSM algorithms have been …
Towards tighter space bounds for counting triangles and other substructures in graph streams
SK Bera, A Chakrabarti - 34th Symposium on Theoretical Aspects …, 2017 - drops.dagstuhl.de
We revisit the much-studied problem of space-efficiently estimating the number of triangles
in a graph stream, and extensions of this problem to counting fixed-sized cliques and cycles …
in a graph stream, and extensions of this problem to counting fixed-sized cliques and cycles …
Linear time subgraph counting, graph degeneracy, and the chasm at size six
We consider the problem of counting all $ k $-vertex subgraphs in an input graph, for any
constant $ k $. This problem (denoted sub-cnt $ _k $) has been studied extensively in both …
constant $ k $. This problem (denoted sub-cnt $ _k $) has been studied extensively in both …