Argument-Based Critics and Recommenders: AQualitative Perspective on User Support Systems

CARLOS IVÁN CHESÑEVAR; ANA MAGUITMAN; GUILLERMO SIMARI,

DATA & KNOWLEDGE ENGINEERING

Elsevier

Lugar: Amsterdam; Año: 2006 vol. -- p. 293 - 319

0169-023X

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 defeasible argumentation framework. The final goal is to enhance practical reasoning capabilities of current user support tools by incorporating argument-based qualitative inference.