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

被引:21
作者
Chesnevar, Carlos Ivan [1 ]
Maguitman, Ana Gabriela
Simari, Guillermo Ricardo
机构
[1] Univ Lleida, Dept Comp Sci, Lleida 25001, Japan
[2] Indiana Univ, Sch Informat, Bloomington, IN 47408 USA
[3] Univ Nacl Sur, Dept Comp Sci & Engn, RA-8000 Bahia Blanca, Buenos Aires, Argentina
关键词
user support systems; decision support systems; recommender systems; critics; defeasible argumentation; practical reasoning;
D O I
10.1016/j.datak.2005.09.005
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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. (c) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码:293 / 319
页数:27
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