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Titlebook: Complex Networks & Their Applications XII; Proceedings of The T Hocine Cherifi,Luis M. Rocha,Murat Donduran Conference proceedings 2024 The

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樓主: Dangle
11#
發(fā)表于 2025-3-23 11:15:57 | 只看該作者
Classification Supported by?Community-Aware Node Featuresnetworks, affecting properties of their nodes. In this paper, we propose a family of community-aware node features and then investigate their properties. We show that they have high predictive power for classification tasks. We also verify that they contain information that cannot be recovered compl
12#
發(fā)表于 2025-3-23 16:35:31 | 只看該作者
13#
發(fā)表于 2025-3-23 19:37:43 | 只看該作者
14#
發(fā)表于 2025-3-24 00:09:59 | 只看該作者
Detecting Community Structures in?Patients with?Peripheral Nervous System Disordersomes even more formidable in bipartite networks. The focus of this study is the patients with problems in their Peripheral Nerve System. To this aim, we engaged the assistance of spinal specialty clinics in the collection of necessary Data. We employ the bipartite network to represent the relationsh
15#
發(fā)表于 2025-3-24 05:10:19 | 只看該作者
Community Detection in?Feature-Rich Networks Using Gradient Descent Approachtegy to recover communities in feature-rich networks. Our adoption of this strategy did not lead to promising results, and thus to improve them, we propose a special “refinement” mechanism, which culls out potentially misleading objects during the optimization. We validated and compared our proposed
16#
發(fā)表于 2025-3-24 09:30:12 | 只看該作者
Detecting Strong Cliques in?Co-authorship Networkstures representing a small group of people or other entities who share common characteristics and know each other. Clique detection algorithms can be applied in all domains where networks are used to describe relationships among entities. That is not only in social, information, or communication net
17#
發(fā)表于 2025-3-24 11:16:15 | 只看該作者
Mosaic Benchmark Networks: Modular Link Streams for?Testing Dynamic Community Detection Algorithmsighly detailed temporal networks such as link streams, studying community structures becomes more complex due to increased data precision and time sensitivity. Despite numerous algorithms developed in the past decade for dynamic community discovery, assessing their performance on link streams remain
18#
發(fā)表于 2025-3-24 17:37:00 | 只看該作者
Entropic Detection of?Chromatic Community Structuresns of people, molecules or processes within a network. The issue is to provide a network partition representative of this organization so that each community presumably gathers nodes sharing a common mission, purpose or property. Usually, this identification is based on the difference in connectivit
19#
發(fā)表于 2025-3-24 19:49:30 | 只看該作者
20#
發(fā)表于 2025-3-25 03:12:44 | 只看該作者
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