Results 1 to 10 of about 1,396 (204)
DotMotif: an open-source tool for connectome subgraph isomorphism search and graph queries [PDF]
Scientific Reports, 2021 Recent advances in neuroscience have enabled the exploration of brain structure at the level of individual synaptic connections. These connectomics datasets continue to grow in size and complexity; methods to search for and identify interesting graph ...
Jordan K. Matelsky +6 more
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Static graph challenge: Subgraph isomorphism [PDF]
2017 IEEE High Performance Extreme Computing Conference (HPEC), 2017 The rise of graph analytic systems has created a need for ways to measure and compare the capabilities of these systems. Graph analytics present unique scalability difficulties. The machine learning, high performance computing, and visual analytics communities have wrestled with these difficulties for decades and developed methodologies for creating ...
Samsi, Siddharth +11 more
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An Efficient Subgraph Isomorphism Solver for Large Graphs
IEEE Access, 2021 For a given pair of pattern and data graphs, the subgraph isomorphism finding problem locates all instances of the pattern graph into the data graph. For a given subgraph isomorphic image of the pattern graph in a data graph, the set of all ordered pairs
Zubair Ali Ansari +2 more
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Isomorphic Subgraph Search Algorithm Based on Neighborhood Equivalence Class [PDF]
Jisuanji gongcheng, 2017 Node heterogeneous graph is often used as a data model for complex networks.Isomorphic subgraph search is an important problem in heterogeneous graph mining,but existing algorithms have shortcomings in subgraph removal,which reduces the efficiency of ...
ZHANG Yutong,WANG Simeng,CAO Jia
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HyGraph: a subgraph isomorphism algorithm for efficiently querying big graph databases
Journal of Big Data, 2022 The big graph database provides strong modeling capabilities and efficient querying for complex applications. Subgraph isomorphism which finds exact matches of a query graph in the database efficiently, is a challenging problem.
Merve Asiler, Adnan Yazıcı, Roy George
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Temporal subgraph isomorphism [PDF]
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2013 Temporal information is increasingly available with network data sets. This information can expose underlying processes in the data via sequences of link activations. Examples range from the propagation of ideas through a scientific collaboration network, to the spread of disease via contacts between infected and susceptible individuals.
Ursula Redmond, Pádraig Cunningham
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Neural Subgraph Isomorphism Counting [PDF]
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2020 In this paper, we study a new graph learning problem: learning to count subgraph isomorphisms. Different from other traditional graph learning problems such as node classification and link prediction, subgraph isomorphism counting is NP-complete and requires more global inference to oversee the whole graph.
Liu, Xin +5 more
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A Zero Knowledge Authentication Protocol Based on Novel Heuristic Algorithm of Dense Induced Subgraphs Isomorphism [PDF]
Engineering and Technology Journal, 2015 Graphs provide an useful mathematical tool for modeling various real world phenomena. Dense graphs arise in many places of interest, for instance the internet and social networks to name just two. The density of a graph should be a real number reflecting
N. M. G. Al-Saidi +2 more
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Infinite limits and folding [PDF]
Discrete Mathematics & Theoretical Computer Science, 2005 We study infinite limits of graphs generated by the duplication model for biological networks. We prove that with probability 1, the sole nontrivial connected component of the limits is unique up to isomorphism. We describe certain infinite deterministic
Anthony Bonato, Jeannette Janssen
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Learning with Small Data: Subgraph Counting Queries
Data Science and Engineering, 2023 Deep Learning (DL) has been widely used in many applications, and its success is achieved with large training data. A key issue is how to provide a DL solution when there is no large training data to learn initially.
Kangfei Zhao +3 more
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