Signal2Symbol: Neuro-Symbolic Temporal Reasoning for Explainable Physiological Time-Series Anomaly Detection
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Abstract
The paper presents Signal2Symbol, a neuro-symbolic framework for explainable anomaly detection in physiological time-series data.
Reality Card
Signal2Symbol effectively converts physiological signals into symbolic sequences and utilizes rare itemset mining and Allen interval algebra to provide interpretable temporal explanations for detected anomalies.
The framework demonstrates robustness under additive noise and baseline-wander perturbations, highlighting the effectiveness of neuro-symbolic tokenization for temporal anomaly analysis.
The paper does not specify the authors or provide detailed reproducibility guidelines, which may limit practical implementation.
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