Semantics and Anomaly Preserving Sampling Strategy (PASS)

PASS (Preserving Anomaly and Semantics Sampling) is a specialized data reduction and sampling strategy that reduces data for the visualization of large-scale time series data as a line chart.

In this repository, all the experiment codes and the results of Semantics and Anomaly Preserving Sampling Strategy (PASS) for Large-Scale Time Series Data have been provided in the following folders.

1. Dataset wise Implementation
2. Image similarity check
3. Measured Correlation
4. Other figures from the Experiment
5. User Study Code with Results