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Related papers: Temporal Matching

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Given a graph $G=(V, E)$, a connected sides cut $(U, V\backslash U)$ or $\delta (U)$ is the set of edges of E linking all vertices of U to all vertices of $V\backslash U$ such that the induced subgraphs $G[U]$ and $G[V\backslash U]$ are…

Data Structures and Algorithms · Computer Science 2017-03-21 Brahim Chaourar

We recently introduced a formalism for the modeling of temporal networks, that we call stream graphs. It emphasizes the streaming nature of data and allows rigorous definitions of many important concepts generalizing classical graphs. This…

Social and Information Networks · Computer Science 2021-11-24 Matthieu Latapy , Clémence Magnien , Tiphaine Viard

We introduce temporal flows on temporal networks, i.e., networks the links of which exist only at certain moments of time. Such networks are ephemeral in the sense that no link exists after some time. Our flow model is new and differs from…

Data Structures and Algorithms · Computer Science 2017-01-23 Eleni C. Akrida , Jurek Czyzowicz , Leszek Gasieniec , Lukasz Kuszner , Paul G. Spirakis

Within many real-world networks the links between pairs of nodes change over time. Thus, there has been a recent boom in studying temporal graphs. Recognizing patterns in temporal graphs requires a proximity measure to compare different…

Machine Learning · Computer Science 2020-07-07 Vincent Froese , Brijnesh Jain , Rolf Niedermeier , Malte Renken

In this paper, we study the problem of finding a maximum matching in the semi-streaming model when edges arrive in a random order. In the semi-streaming model, an algorithm receives a stream of edges and it is allowed to have a memory of…

Data Structures and Algorithms · Computer Science 2019-12-24 Alireza Farhadi , MohammadTaghi Hajiaghayi , Tung Mai , Anup Rao , Ryan A. Rossi

We formalize networks with evolving structures as temporal networks and propose a generative link prediction model, Generative Link Sequence Modeling (GLSM), to predict future links for temporal networks. GLSM captures the temporal link…

Machine Learning · Computer Science 2020-04-28 Yue Wang , Chenwei Zhang , Shen Wang , Philip S. Yu , Lu Bai , Lixin Cui , Guandong Xu

Finding a maximum-cardinality or maximum-weight matching in (edge-weighted) undirected graphs is among the most prominent problems of algorithmic graph theory. For $n$-vertex and $m$-edge graphs, the best known algorithms run in…

Data Structures and Algorithms · Computer Science 2021-05-10 Tomohiro Koana , Viatcheslav Korenwein , André Nichterlein , Rolf Niedermeier , Philipp Zschoche

Modularity is a very widely used measure of the level of clustering or community structure in networks. Here we consider a recent generalisation of the definition of modularity to temporal graphs, whose edge-sets change over discrete…

Combinatorics · Mathematics 2025-07-24 Vilhelm Agdur , Jessica Enright , Laura Larios-Jones , Kitty Meeks , Fiona Skerman , Ella Yates

Graph theory provides a language for studying the structure of relations, and it is often used to study interactions over time too. However, it poorly captures the both temporal and structural nature of interactions, that calls for a…

Social and Information Networks · Computer Science 2017-10-12 Matthieu Latapy , Tiphaine Viard , Clémence Magnien

A graph is temporally connected if there exists a strict temporal path, i.e. a path whose edges have strictly increasing labels, from every vertex $u$ to every other vertex $v$. In this paper we study temporal design problems for undirected…

Data Structures and Algorithms · Computer Science 2022-05-03 Nina Klobas , George B. Mertzios , Hendrik Molter , Paul G. Spirakis

Estimating the size of the maximum matching is a canonical problem in graph algorithms, and one that has attracted extensive study over a range of different computational models. We present improved streaming algorithms for approximating…

Data Structures and Algorithms · Computer Science 2016-11-15 Graham Cormode , Hossein Jowhari , Morteza Monemizadeh , S. Muthukrishnan

Graphs are found in a plethora of domains, including online social networks, the World Wide Web and the study of epidemics, to name a few. With the advent of greater volumes of information and the need for continuously updated results under…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-12-19 Miguel E. Coimbra , Sérgio Esteves , Alexandre P. Francisco , Luís Veiga

Graph matching is the process of computing the similarity between two graphs. Depending on the requirement, it can be exact or inexact. Exact graph matching requires a strict correspondence between nodes of two graphs, whereas inexact…

Social and Information Networks · Computer Science 2022-01-13 Shri Prakash Dwivedi

A temporal graph can be considered as a stream of links, each of which represents an interaction between two nodes at a certain time. On temporal graphs, link prediction is a common task, which aims to answer whether the query link is true…

Artificial Intelligence · Computer Science 2024-02-13 Bingqing Liu , Xikun Huang

Dynamic networks have intrinsic structural, computational, and multidisciplinary advantages. Link prediction estimates the next relationship in dynamic networks. However, in the current link prediction approaches, only bipartite or…

Social and Information Networks · Computer Science 2020-06-09 Mohamoud Ali , Yugyung Lee , Praveen Rao

Analyzing the groups in the network based on same attributes, functions or connections between nodes is a way to understand network information. The task of discovering a series of node groups is called community detection. Generally, two…

Social and Information Networks · Computer Science 2021-01-14 Shuhan Yan , Yuting Jia , Xinbing Wang

A graph stream is a continuous sequence of data items, in which each item indicates an edge, including its two endpoints and edge weight. It forms a dynamic graph that changes with every item in the stream. Graph streams play important…

Data Structures and Algorithms · Computer Science 2018-09-06 Xiangyang Gou , Lei Zou , Chenxingyu Zhao , Tong Yang

We consider the problem of assigning appearing times to the edges of a digraph in order to maximize the (average) temporal reachability between pairs of nodes. Motivated by the application to public transit networks, where edges cannot be…

Discrete Mathematics · Computer Science 2025-01-22 Filippo Brunelli , Pierluigi Crescenzi , Laurent Viennot

Temporal graphs are graphs whose edges are only present at certain points in time. Reachability in these graphs relies on temporal paths, where edges are traversed chronologically. A temporal graph that offers all-pairs reachability is said…

Computational Complexity · Computer Science 2026-04-28 Arnaud Casteigts , Christian Komusiewicz , Nils Morawietz

{\it SimRank} is a classic measure of the similarities of nodes in a graph. Given a node $u$ in graph $G =(V, E)$, a {\em single-source SimRank query} returns the SimRank similarities $s(u, v)$ between node $u$ and each node $v \in V$. This…

Data Structures and Algorithms · Computer Science 2019-05-08 Zhewei Wei , Xiaodong He , Xiaokui Xiao , Sibo Wang , Yu Liu , Xiaoyong Du , Ji-Rong Wen