Distributed stock exchange scenario using artificial emotional knowledge

The current globalization and distribution of markets has meant that companies and organizations frequently need to adapt their internal structure and operating processes, in order to demonstrate efficiency and effectiveness for every customers and users, specially when considering aspects that are beyond logical definitions, such as the emotions. To cope with that, this work proposes an alternative to model the distributed Stock Exchange Scenario with ontologies. The proposed model considers that each investor can invest using information obtained by communication with different traders or investors. Each investor has its own knowledge represented by ontologies, which is composed by technical knowledge together with internal emotional states. Our preliminary results, shows the possibility to use ontologies as knowledge representation mechanisms for domains that consider the human emotional dimension for decision-making processes.