Key Value Sequence

Key-value sequences, ubiquitous in data representing diverse processes like online purchasing or network traffic, are increasingly studied for their efficient classification. Current research focuses on developing methods that accurately classify these sequences while minimizing processing time, particularly addressing the challenge of "tangled" sequences where multiple concurrent processes are intertwined. Advanced algorithms leverage both intra- and inter-sequence correlations to improve representation learning and prediction accuracy, leading to significant improvements in applications like user profiling and anomaly detection. These advancements are crucial for real-time decision-making in various domains.