Anchor Graph Structure Fusion

Anchor graph structure fusion integrates information from multiple data sources (views) by representing each view as a graph and then combining these graphs to improve clustering or similarity search. Current research focuses on aligning anchor points—representative data samples—across different views to ensure accurate fusion, often employing novel algorithms that leverage both feature and structural information for improved correspondence. This approach is significant for handling large-scale datasets and improving the performance of multi-view clustering and cross-modal retrieval tasks, offering more robust and efficient solutions compared to methods that treat each view independently.