spartan2: a developing open-sourced graph and time series mining package based on sparse tensor/matrix and sequential analysis.

spartan2 is a collection of data mining algorithms on big graphs and time series, providing three basic tasks: anomaly detection, forecast, and summarization.

Graphs and time series are fundamental representations of many key applications in a wide range of

• online user behaviors, e.g. following in social media, shopping, and downloading Apps,
• finance, e.g. stock tradings, and bank transfers,
• sensor networks, e.g. sensor readings, and smart power grid, and
• health, e.g. electrocardiogram, photoplethysmogram, and respiratory inductance plethysmography.

In practice, we find that thinking graphs and time series as matrices or tensors can enable us to find efficient (near linear), interpretable, yet accurate solutions in many applications. Therefore, our goal is developping a collectioin of algorithms on graphs and time series based on tensors (matrix is a 2-mode tensor).

In real world, those tensors are sparse, and we are required to make use of the sparsity to develop efficient algorithms. That is why we name the package as spartan: sparse tensor analytics.

The package named spartan can be imported and run independently as a usual python package. Everything in package spartan is viewed as a tensor (sparse).