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.

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doi.org/10.1109/EISIC.2016.026, hdl.handle.net/1765/99133
7th European Intelligence and Security Informatics Conference, EISIC 2016
Rotterdam School of Management (RSM), Erasmus University

Orphanides, C., Akhgar, B., & Bayerl, S. (2017). Discovering knowledge in online drug transactions using conceptual graphs and formal concept analysis. In Proceedings - 2016 European Intelligence and Security Informatics Conference, EISIC 2016 (pp. 100–103). doi:10.1109/EISIC.2016.026