Popular approaches to building data from unstructured text come with limitations, such as scalability, interpretability, replicability, and real-world applicability. These can be overcome with Context Rule Assisted Machine Learning (CRAML), a method and no-code suite of software tools that...

We provide a better understanding of the causal structure in a multivariate time series by introducing a novel statistical procedure for testing indirect and spurious causal effects. In practice, detecting these effects is a complicated task, since the auxiliary variables that transmit/induce...

The COVID-19 pandemic underscores the critical need for detailed, timely information on its evolving economic impacts, particularly for Sub-Saharan Africa (SSA) where data availability and lack of generalizable nowcasting methodologies limit efforts for coordinated policy responses. This paper...

1. Defining Knowledge Technology and Systems -- 2. Big Data Analytics in Healthcare -- 3. Knowledge Discovery from Online Review -- 4. Machine Learning for Solving Unstructured Problems -- 5. Qualitative Modeling to Extract Knowledge for Problem Structuring -- 6. Agent-Based Simulation of Low...