Graph Model: A representation of conflict scenarios as a network of nodes and edges, where nodes denote possible states and edges represent transitions due to decision makers’ actions.

After realising I needed a way to generate topic models from a range of text attributes, I set out to explore several popular tools to see which one would best suit my needs.

In this article, we propose a new data-analytic approach to measure firms’ dyadic business proximity. Specifically, our method analyzes the unstructured texts that describe firms’ businesses using the ...

Neo4j was among the first graph databases to expand its offering to data scientists, and Eifrem went as far as to predict that by 2030, every machine learning model will use relationships as a signal.

In cases where the models were incorrectly adding “conceptually spurious” words to certain topics, we encouraged the models to pull the undesirable words out of our good topics by adding them to a ...

A multivariate Gaussian graphical Markov model for an undirected graph G, also called a covariance selection model or concentration graph model, is defined in terms of the Markov properties, i.e.