In the context of content-based recommender systems, the aim of this paper is to determine how better profiles can be built and how these affect the recommendation process based on the incorporation of temporality, i.e. the inclusion of time in the recommendation process, and topicality, i.e. the representation of texts associated with users and items using topics and their combination. The main contribution of the paper is to present two different ways of hybridising these two dimensions and to evaluate and compare them with other alternatives.

翻译：在基于内容的推荐系统背景下，本文旨在探究如何构建更优的用户档案，以及这些档案如何通过融入时间性（即在推荐过程中引入时间因素）和主题性（即利用主题及其组合来表示与用户和物品相关的文本）来影响推荐过程。本文的主要贡献在于提出了混合这两种维度的两种不同方法，并与其他替代方案进行了评估和比较。