info:eu-repo/semantics/article
Guidelines for the Analysis and Design of Argumentation-Based Recommendation Systems
Fecha
2020-09-01Registro en:
Leiva, Mario Alejandro; Budan, Maximiliano Celmo David; Simari, Gerardo; Guidelines for the Analysis and Design of Argumentation-Based Recommendation Systems; IEEE Computer Society; Ieee Intelligent Systems; 35; 5; 1-9-2020; 28-37
1541-1672
1941-1294
CONICET Digital
CONICET
Autor
Leiva, Mario Alejandro
Budan, Maximiliano Celmo David
Simari, Gerardo
Resumen
Recommender systems study the characteristics of its users and applying different kinds of processing to the available data, find a subset of items that may be of interest to a given user in a specific situation. Argumentation-based tools offer the possibility of analyzing complex and dynamic domains by generating and analyzing arguments for and against recommending a specific item based on the users' preferences. This approach allows us to analyze the qualitative and quantitative characteristics of the recommended items, and to provide explanations to increase transparency. In this article, we develop a set of software engineering guidelines for the analysis and design of recommender systems leveraging this approach.