Results 11 to 20 of about 358,315 (287)
Searching for metastable particles using graph computing
Scientific Reports, 2021 The reconstruction of charged particle trajectories at the Large Hadron Collider and future colliders relies on energy depositions in sensors placed at distances ranging from a centimeter to a meter from the colliding beams.
Ashutosh V. Kotwal
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Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2015 Modern Web data is highly structured in terms of entities and relations from large knowledge resources, geo-temporal references and social network structure, resulting in a massive multidimensional graph. This graph essentially unifies both the searcher and the information resources that played a fundamentally different role in traditional IR, and ...
Alonso, O., Hearst, M.A., Kamps, J.
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Searching Correlated Patterns From Graph Streams
IEEE Access, 2020 Mining the correlation has attracted widespread attention in the research community because of its advantages in understanding the dependencies between objects.
Ming Jin, Mei Li, Yu Zheng, Lianhua Chi
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DotMotif: an open-source tool for connectome subgraph isomorphism search and graph queries
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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GRAPES: a software for parallel searching on biological graphs targeting multi-core architectures. [PDF]
PLoS ONE, 2013 Biological applications, from genomics to ecology, deal with graphs that represents the structure of interactions. Analyzing such data requires searching for subgraphs in collections of graphs. This task is computationally expensive.
Rosalba Giugno +5 more
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KVGCN: A KNN Searching and VLAD Combined Graph Convolutional Network for Point Cloud Segmentation
Remote Sensing, 2021 Semantic segmentation of the sensed point cloud data plays a significant role in scene understanding and reconstruction, robot navigation, etc. This work presents a Graph Convolutional Network integrating K-Nearest Neighbor searching (KNN) and Vector of ...
Nan Luo +6 more
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Co-Attention Graph Pooling for Efficient Pairwise Graph Interaction Learning
IEEE Access, 2023 Graph Neural Networks (GNNs) have proven to be effective in processing and learning from graph-structured data. However, previous works mainly focused on understanding single graph inputs while many real-world applications require pair-wise analysis for ...
Junhyun Lee +3 more
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Binary Search in Graphs Revisited [PDF]
Algorithmica, 2018 In the classical binary search in a path the aim is to detect an unknown target by asking as few queries as possible, where each query reveals the direction to the target. This binary search algorithm has been recently extended by [Emamjomeh-Zadeh et al., STOC, 2016] to the problem of detecting a target in an arbitrary graph. Similarly to the classical
Deligkas, A. +2 more
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Influential Attributed Communities via Graph Convolutional Network (InfACom-GCN)
Information, 2022 Community search is a basic problem in graph analysis. In many applications, network nodes have certain properties that are important for the community to make sense of the application; hence, attributes are associated with nodes to capture their ...
Nariman Adel Hussein +2 more
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Information and Computation, 2012 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Barrière, Lali +6 more
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