JACIII Vol.9 No.1 pp. 53-60
doi: 10.20965/jaciii.2005.p0053


Combining Argumentation and Web Search Technology: Towards a Qualitative Approach for Ranking Results

Carlos Iván Chesñevar*, and Ana Gabriela Maguitman**

*Department of Computer Science, University of Lleida, 25001 Lleida, Spain

**Computer Science Department, Indiana University, Bloomington, IN 47405-7104, USA

November 18, 2004
November 22, 2004
January 20, 2005
recommender systems, defeasible argumentation, decision support systems

Several techniques for improving web search have been developed over the last years. Most existing approaches are still limited, mainly due to the absence of qualitative criteria for ranking results and insensitivity to user preferences for guiding the search. At the same time, defeasible argumentation 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 ARGUENET, a recommender system that classifies search results according to preference criteria declaratively specified by the user. The proposed approach integrates a traditional web search engine with a defeasible argumentation framework.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, IE9,10,11, Opera.

Last updated on Apr. 19, 2018