Defeasible reasoning and decision support systems
Decision Support Systems
EVID: a system for interactive defeasible reasoning
Decision Support Systems - Special issue on logic modeling
Abstract argumentation systems
Artificial Intelligence
Implications of buyer decision theory for design of e-commerce websites
International Journal of Human-Computer Studies
Introduction: DSS: Directions for the next decade
Decision Support Systems - Special issue: Decision support systems: Directions for the next decade
Past, present, and future of decision support technology
Decision Support Systems - Special issue: Decision support systems: Directions for the next decade
WI '01 Proceedings of the First Asia-Pacific Conference on Web Intelligence: Research and Development
ATAL '99 6th International Workshop on Intelligent Agents VI, Agent Theories, Architectures, and Languages (ATAL),
Defeasible logic programming: an argumentative approach
Theory and Practice of Logic Programming
Argumentation-based negotiation
The Knowledge Engineering Review
Decision station: situating decision support systems
Decision Support Systems
Induction of defeasible logic theories in the legal domain
ICAIL '03 Proceedings of the 9th international conference on Artificial intelligence and law
Guest Editorial: Argumentation in Multi-Agent Systems
Autonomous Agents and Multi-Agent Systems
DR-Prolog: A System for Defeasible Reasoning with Rules and Ontologies on the Semantic Web
IEEE Transactions on Knowledge and Data Engineering
DR-BROKERING: A semantic brokering system
Knowledge-Based Systems
Argument-based critics and recommenders: a qualitative perspective on user support systems
Data & Knowledge Engineering - Special issue: WIDM 2004
Progress in Web-based decision support technologies
Decision Support Systems
Laying the foundations for a World Wide Argument Web
Artificial Intelligence
Harnessing Ontologies for Argument-Based Decision-Making in Breast Cancer
ICTAI '07 Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence - Volume 02
A knowledge-based decision support system for measuring enterprise performance
Knowledge-Based Systems
On Extending RuleML for Modal Defeasible Logic
RuleML '08 Proceedings of the International Symposium on Rule Representation, Interchange and Reasoning on the Web
Business stakeholder analyzer: An experiment of classifying stakeholders on the Web
Journal of the American Society for Information Science and Technology
Reasoning about preferences in argumentation frameworks
Artificial Intelligence
Argument-based learning communities
Knowledge-Based Systems
Argumentation in Artificial Intelligence
Argumentation in Artificial Intelligence
Decider: A fuzzy multi-criteria group decision support system
Knowledge-Based Systems
Expert Systems with Applications: An International Journal
A research framework for Web-based open decision support systems
Knowledge-Based Systems
REASONING WITH INCONSISTENT ONTOLOGIES THROUGH ARGUMENTATION
Applied Artificial Intelligence - Knowledge Representation and Ontology Research
GECON'07 Proceedings of the 4th international conference on Grid economics and business models
The hedgehog and the fox: an argumentation-based decision support system
ArgMAS'07 Proceedings of the 4th international conference on Argumentation in multi-agent systems
Web-based Support Systems
Using argumentation to model and deploy agent-based B2B applications
Knowledge-Based Systems
A Dynamic Argumentation Framework
Proceedings of the 2010 conference on Computational Models of Argument: Proceedings of COMMA 2010
An extended TOPSIS for determining weights of decision makers with interval numbers
Knowledge-Based Systems
Development of a Logic Layer in the Semantic Web: Research Issues
SKG '10 Proceedings of the 2010 Sixth International Conference on Semantics, Knowledge and Grids
Mining comparative opinions from customer reviews for Competitive Intelligence
Decision Support Systems
Visualizing Semantic Web proofs of defeasible logic in the DR-DEVICE system
Knowledge-Based Systems
Algorithms for fuzzy multi expert multi criteria decision making (ME-MCDM)
Knowledge-Based Systems
ONTOarg: A decision support framework for ontology integration based on argumentation
Expert Systems with Applications: An International Journal
Information Systems Frontiers
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Over the past few decades, there has been a resurgence of interest in using high-level software intelligence for business intelligence (BI). The objective is to produce actionable information that is delivered at the right time, easily comprehendible and exportable to other software to assist business decision-making processes. Although the design and development of decision support systems (DSS) has been carried out for over 40 years, DSS still suffer from many limitations such as poor maintainability, poor flexibility and less reusability. The development of the Internet and WWW has helped information systems to overcome those limitations and Web DSS is now an active area of research in business intelligence, impacting significantly on the way information is exchanged and businesses are conducted. However, to remain competitive, companies rely on business intelligence (BI) to continually monitor and analyze the operating environment (both internal and external), to identify potential risks, and to devise competitive business strategies. However, the current Web DSS applications are not able to reason over information present across organizational boundaries which could be incomplete and conflicting. The use of an argumentation-based mechanism has not been explored to address such shortcomings in Web DSS. Argumentation is a kind of commonsense reasoning used by human beings to reach a justifiable conclusion when available information is incomplete and/or inconsistent among participants. In this paper, we propose and elaborate in detail a conceptual framework and formal argumentation-based semantics for Web enabled Intelligent DSS (Web@IDSS). We evaluate the use of argumentative reasoning in Web DSS with the help of a case study, prototype development and future directions. Applications built according to the proposed framework will provide more practical, understandable results to decision makers.