Showing 301 - 320 results of 643 for search 'Graph research algorithm', query time: 0.13s Refine Results
  1. 301

    A Macroscopic Exploration of the Ideoscape on Exosomes for Bone Regeneration by Maria Teresa Colangelo, Marco Meleti, Stefano Guizzardi, Carlo Galli

    Published 2024-10-01
    “…<b>Conclusions:</b> This study exemplifies the utility of combining topic modeling with knowledge graph creation to map research trends, offering a flexible and largely automated tool for researchers to explore the vast bodies of literature and guide future research directions.…”
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    A Monte Carlo Tree Search approach to QAOA: finding a needle in the haystack by Andoni Agirre, Evert van Nieuwenburg, Matteo M Wauters

    Published 2025-01-01
    “…The search for quantum algorithms to tackle classical combinatorial optimization problems has long been one of the most attractive yet challenging research topics in quantum computing. …”
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    Image key information processing using convolutional neural network and rotational invariant-hierarchical max pooling algorithm. by Guangmei Ma

    Published 2025-01-01
    “…The feature extraction layer was structurally supplemented and expressed at multiple scales in a two-dimensional linear graph. In the method training loss test, the research method achieved a loss value that dropped to near 0 after 32 iterations when training in low-contrast images. …”
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    Incorporating echo state network and sand cat swarm optimization algorithm based on quantum for named entity recognition by Fang Huang, Baocheng Wang, Jafar Safarzadeh

    Published 2025-05-01
    “…Additionally, the neural network was optimized utilizing the quantum-based sand cat swarm optimization algorithm. Eventually, CRF was employed to produce the predicted sequence of labels. …”
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    Article
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    Application Research of Cross-Attention Mechanism for Traffic Prediction Based on Heterogeneous Data by Feng Zhihao

    Published 2025-01-01
    “…Through an analysis of these methods, the research demonstrates how applying advanced deep learning algorithms and cross-attention processes has significantly improved prediction robustness and accuracy. …”
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    ProvNavigator: shadow path guided attack investigation method by XI Hao, FAN Hao, YUAN Shenyang, ZHU Jinyu, CHEN Changhua, WAN Hai, ZHAO Xibin

    Published 2025-04-01
    “…Currently, provenance graph-based techniques have become mainstream methods, but these methods face the challenge of dependency explosion problems. …”
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  15. 315

    Language model-enhanced edge factor mining in citation network by WANG Minmao, ZHAO Hongke, WU Likang, JIAO Zhixian, HUANG Zhenya

    Published 2025-03-01
    “…Fine-grained factor mining used the K-means clustering algorithm to capture more detailed semantic topic-level edge factors from graph textual data. …”
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  16. 316

    Language model-enhanced edge factor mining in citation network by WANG Minmao, ZHAO Hongke, WU Likang, JIAO Zhixian, HUANG Zhenya

    Published 2025-03-01
    “…Fine-grained factor mining used the K-means clustering algorithm to capture more detailed semantic topic-level edge factors from graph textual data. …”
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    Article
  17. 317

    Travel route recommendation with a trajectory learning model by Xiangping Wu, Zheng Zhang, Wangjun Wan

    Published 2024-11-01
    “…Finally, a beam search algorithm is applied to generate and recommend multiple candidate routes. …”
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    Article
  18. 318

    MODIFIED WEIGHT MATRIX USING PRIM’S ALGORITHM IN MINIMUM SPANNING TREE (MST) APROACH FOR GSTAR(1;1) MODEL by Nur'ainul Miftahul Huda, Fransiskus Fran, Yundari Yundari, Lisa Fikadila, Fauziah Safitri

    Published 2023-04-01
    “…Before starting Prim's algorithm, the correlation is first utilized as an input in forming the initial graph. …”
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    Missing value interpolation algorithm for long-term temperature observation data based on data augmentation multiple interpolation method by Xiaolin Liu, Bo Wang, Shuanglong Jin, Zongpeng Song

    Published 2025-09-01
    “…The noise reduction method based on Graph Attention Network (GAT) is adopted to handle the noise in the data. …”
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    Article