GNN Model Based On Node Classification Forecasting in Social Network

Awasthi, A. K.; Garov, Arun Kumar; Sharma, Minakshi; Sinha, Mrigank

doi:10.1109/aisc56616.2023.10085118

Cited by 7 publications

(1 citation statement)

References 23 publications

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“…It specializes in performing a variety of graph network related tasks, such as link prediction, node classification, graph generation, etc., by effectively capturing the features and topology of nodes and edges in the graph. For example, by constructing heterogeneous GNNs, we can mine the potential relationships among various entity types; by constructing dynamic GNNs, we can deal with the problem of time-varying relationships among entities [46]. In the metaverse, supported by GNN technology, users' social behaviors and patterns can be dynamically analyzed.…”

Section: Fig 8 Application Of Aigc In Game Designmentioning

confidence: 99%

Managing Metaverse Data Tsunami: Actionable Insights

Zhang,

Chen,

Ooi

et al. 2024

IEEE Trans. Knowl. Data Eng.

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In the metaverse the physical space and the virtual space co-exist, and interact simultaneously. While the physical space is virtually enhanced with information, the virtual space is continuously refreshed with real-time, real-world information.To allow users to process and manipulate information seamlessly between the real and digital spaces, novel technologies must be developed. These include smart interfaces, new augmented realities, and efficient data storage, management, and dissemination techniques. In this paper, we first discuss some promising cospace applications. These applications offer opportunities that neither of the spaces can realize on its own. Then, we further discuss several emerging technologies that empower the construction of metaverse. After that, we discuss comprehensively the data centric challenges. Finally, we discuss and envision what are likely to be required from the database and system perspectives.

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Section: Fig 8 Application Of Aigc In Game Designmentioning

confidence: 99%