wanxinhang/AAAI-2023-AWMVC
The code of AAAI 2023 ''Auto-Weighted Multi-View Clustering for Large-Scale Data''
This tool helps researchers and data scientists automatically group complex, multi-faceted datasets without needing to manually assign importance to each data perspective. It takes in large-scale data that has been observed from multiple angles (e.g., images with color, texture, and shape features) and outputs organized clusters, simplifying the analysis of intricate patterns. This is ideal for those working with diverse data sources where underlying groupings are not immediately obvious.
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Use this if you need to find inherent clusters within large datasets that have multiple distinct 'views' or feature sets, without spending time fine-tuning how each view contributes to the clustering.
Not ideal if your data is small-scale, has only a single set of features, or if you require explicit control over the weighting of different data views during the clustering process.
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Sep 15, 2025
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