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Data & Knowledge Engineering
Volume 59, Issue 2, November 2006, Pages 293-319
Including: Sixth ACM International Workshop on Web Information and Data Management
 
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doi:10.1016/j.datak.2005.09.005    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2005 Elsevier B.V. All rights reserved.

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

Carlos Iván Chesñevara, Corresponding Author Contact Information, E-mail The Corresponding Author, Ana Gabriela Maguitmanb, E-mail The Corresponding Author and Guillermo Ricardo Simaric, E-mail The Corresponding Author

aDepartment of Computer Science, Universitat de Lleida, C/Jaume II, 69, 25001 Lleida, Spain bSchool of Informatics, Indiana University, Bloomington, IN 47408-3912, USA cDepartment of Computer Science and Engineering, Universidad Nacional del Sur, 8000 B. Blanca, Argentina

Received 25 April 2005; 
revised 7 September 2005; 
revised 7 September 2005. 
Available online 27 October 2005.

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

Keywords: User support systems; Decision support systems; Recommender systems; Critics; Defeasible argumentation; Practical reasoning

Article Outline

1. Introduction and motivations
2. User support systems
2.1. Critics
2.2. Recommenders
3. Modelling argumentation in DeLP
3.1. Argumentation in AI: background
3.2. Defeasible logic programming
4. Enhancing user support system with defeasible argumentation
5. An argument-based Web recommender
5.1. Providing recommendations for Web search queries: a worked example
6. An argument-based word processing critic
6.1. An example of language usage assessment
7. Implementation issues. Ongoing work
8. Related work
9. Conclusions
Acknowledgements
References
Vitae













Data & Knowledge Engineering
Volume 59, Issue 2, November 2006, Pages 293-319
Including: Sixth ACM International Workshop on Web Information and Data Management
 
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