Manolis Tzagarakis
ABSTRACT
Systems supporting argumentation exist for a long time and have appeared with many different forms, ranging from online forums, to mind maps and decision support systems. Such kind of systems are used on a daily basis by teams that collaborate in data intensive and cognitive complex settings, such as for example teams involved in DNA analysis, marketing or drug testing research. In these settings, teams collect big amounts of required data as well as use sophisticated data mining tools to uncover patterns in the collected data. Current argumentation support systems provide little care for integrating data mining tools required by these teams. In this paper, we present an approach that integrates argumentation support systems with data mining services to augment collaboration and decision making in the above teams. Specifically, the proposed approach allows data mining services and their outcomes to be meaningfully used in argumentative discourses. Such integration enables the contextualization of these services, their execution and their respective results by the argumentative discourse, hence greatly facilitating its monitoring and understanding. Moreover, the paper presents how the proposed argumentation system has been developed based on a Component-Based Open Hypermedia System. The overall aim of these efforts is to show that CB-OHSs are an appropriate architecture to develop complex structuring paradigms in the field of argumentation especially in situations that require a synergy between human and machine intelligence.
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Index Terms
- Developing argumentation services based on hypermedia systems
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