Discovering Knowledge in Online Drug Transactions Using Conceptual Graphs and Formal Concept Analysis

In this short paper, we describe a conceptual approach in which Conceptual Graphs (CGs) and Formal Concept Analysis (FCA) are employed towards knowledge discovery in online drug transactions. The transactions are acquired by performing Named-Entity Recognition (NER) on documents crawled from online public sources such as Twitter and Instagram, and are structured based on a CG ontology created to model such transactions. The drug transactions are then visualized using FCA as the knowledge discovery method.