Results 11 to 20 of about 2,151,737 (304)
Temporal Graph Signal Decomposition [PDF]
Knowledge Discovery and Data Mining, 2021 Temporal graph signals are multivariate time series with individual components associated with nodes of a fixed graph structure. Data of this kind arises in many domains including activity of social network users, sensor network readings over time, and ...
M. McNeil, Lin Zhang, P. Bogdanov
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Knowledge Graph Reasoning Based on Tensor Decomposition and MHRP-Learning
Advances in Multimedia, 2021 In the process of learning and reasoning knowledge graph, the existing tensor decomposition technology only considers the direct relationship between entities in knowledge graph. However, it ignores the characteristics of the graph structure of knowledge
Tangsen Huang +3 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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Eulerian Cycle Decomposition Conjecture for the line graph of complete graphs
AKCE International Journal of Graphs and Combinatorics, 2019 The Eulerian Cycle Decomposition Conjecture, by Chartrand, Jordon and Zhang, states that if the minimum number of odd cycles in a cycle decomposition of an Eulerian graph G of size m is a, the maximum number of odd cycles in such a cycle decomposition is
R. Rajarajachozhan, R. Sampathkumar
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LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation [PDF]
International Conference on Learning Representations, 2023 Graph neural network (GNN) is a powerful learning approach for graph-based recommender systems. Recently, GNNs integrated with contrastive learning have shown superior performance in recommendation with their data augmentation schemes, aiming at dealing ...
Xuheng Cai +3 more
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Constrained ear decompositions in graphs and digraphs [PDF]
Discrete Mathematics & Theoretical Computer Science, 2019 Ear decompositions of graphs are a standard concept related to several major problems in graph theory like the Traveling Salesman Problem. For example, the Hamiltonian Cycle Problem, which is notoriously N P-complete, is equivalent to deciding whether a ...
Frédéric Havet, Nicolas Nisse
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End-to-End Learning for Graph Decomposition [PDF]
IEEE International Conference on Computer Vision, 2018 Deep neural networks provide powerful tools for pattern recognition, while classical graph algorithms are widely used to solve combinatorial problems. In computer vision, many tasks combine elements of both pattern recognition and graph reasoning.
Jie Song +4 more
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Tucker decomposition-based Temporal Knowledge Graph Completion [PDF]
Knowledge-Based Systems, 2020 Knowledge graphs have been demonstrated to be an effective tool for numerous intelligent applications. However, a large amount of valuable knowledge still exists implicitly in the knowledge graphs.
Pengpeng Shao +5 more
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Method of Service Decomposition Based on Microservice Architecture [PDF]
Jisuanji kexue, 2021 The microservice decomposition of the monolithic system can effectively alleviate the problems of system redundancy and difficulty in maintenance of the monolithic architecture.However,the existing microservice decomposition methods fail to make full use
JIANG Zheng, WANG Jun-li, CAO Rui-hao, YAN Chun-gang
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Capturing Polynomial Time using Modular Decomposition [PDF]
Logical Methods in Computer Science, 2019 The question of whether there is a logic that captures polynomial time is one of the main open problems in descriptive complexity theory and database theory.
Berit Grußien
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