Multi Aspect

Multi-aspect analysis focuses on understanding complex data with multiple interconnected features or perspectives. Current research emphasizes developing robust methods for handling this complexity, particularly using tensor-based models and graph neural networks to capture intricate relationships within high-dimensional datasets like social media videos and time-evolving networks. These advancements aim to improve data completion in scenarios with missing or under-counted information, enabling more accurate pattern discovery, anomaly detection, and predictive modeling across diverse fields. The resulting insights have significant implications for various applications, including epidemiology, social network analysis, and recommendation systems.