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.

中文翻译：

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基于论证的推荐系统分析和设计指南


推荐系统研究用户的特征并对可用数据应用不同类型的处理，找到特定情况下给定用户可能感兴趣的项目子集。基于论证的工具通过根据用户的偏好生成和分析支持或反对推荐特定项目的论证，提供了分析复杂和动态领域的可能性。这种方法使我们能够分析推荐项目的定性和定量特征，并提供解释以提高透明度。在本文中，我们开发了一套软件工程指南，用于利用这种方法分析和设计推荐系统。