Argument-based critics and recommenders: a qualitative perspective on user support systems

  • Authors:
  • Carlos Iván Chesñevar;Ana Gabriela Maguitman;Guillermo Ricardo Simari

  • Affiliations:
  • Department of Computer Science, Universitat de Lleida, Lleida, Spain;School of Informatics, Indiana University, Bloomington, IN;Department of Computer Science and Engineering, Universidad National del Sur, B. Blanca, Argentina

  • Venue:
  • Data & Knowledge Engineering - Special issue: WIDM 2004
  • Year:
  • 2006

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Abstract

In recent years we have witnessed the wide-spread evolution of support tools that operate in association with the user to accomplish a range of computer-mediated tasks. Two examples of these tools are critics and recommenders. Critics are cooperative tools that observe the user interacting with a computer system and present reasoned opinions about a product under development. Recommender systems are tools that assist users by facilitating access to relevant items. At the same time, defeasible argumentation has evolved as a successful approach in AI to model commonsense qualitative reasoning, with applications in many areas, such as agent theory, knowledge engineering and legal reasoning. This paper presents a novel approach towards the integration of user support systems, such as critics and recommender systems, with a defeasine argumentation framework. The final goal is to enhance practical reasoning capabilities of current user support tools by incorporating argument-based qualitative inference.