We present DEGARI (Dynamic Emotion Generator And ReclassIfier), an explainable system for emotion attribution and recommendation. This system relies on a recently introduced commonsense reasoning framework, the ${\mathbf{T}}^{\mathsf{CL}}$ logic, which is based on a human-like procedure for the automatic generation of novel concepts in a Description Logics knowledge base. Starting from an ontological formalization of emotions based on the Plutchik model, known as ArsEmotica, the system exploits the logic ${\mathbf{T}}^{\mathsf{CL}}$ to automatically generate novel commonsense semantic representations of compound emotions (e.g. Love as derived from the combination of Joy and Trust according to Plutchik). The generated emotions correspond to prototypes, i.e. commonsense representations of given concepts, and have been used to reclassify emotion-related contents in a variety of artistic domains, ranging from art datasets to the editorial contents available in RaiPlay, the online platform of RAI Radiotelevisione Italiana (the Italian public broadcasting company). We show how the reported results (evaluated in the light of the obtained reclassifications, the user ratings assigned to such reclassifications, and their explainability) are encouraging, and pave the way to many further research directions.

我们提出了 DEGARI（Dynamic Emotion Generator And ReclassIfier），这是一个可解释的情感归因和推荐系统。该系统依赖于最近引入的常识推理框架，${\mathbf{吨}}^{\mathsf{CL}}$逻辑，它基于在描述逻辑知识库中自动生成新概念的类人程序。从基于 Plutchik 模型（称为 ArsEmotica）的情绪本体形式化开始，该系统利用了逻辑${\mathbf{吨}}^{\mathsf{CL}}$自动生成复合情绪的新颖常识语义表示（例如，根据 Plutchik 的说法，爱源自喜悦和信任的组合）。生成的情感对应于原型，即给定概念的常识表示，并已被用于对各种艺术领域中与情感相关的内容进行重新分类，从艺术数据集到 RAI Radiotelevisione Italiana 的在线平台 RaiPlay 中可用的编辑内容（意大利公共广播公司）。我们展示了报告的结果（根据获得的重分类、分配给此类重分类的用户评分及其可解释性进行评估）是如何令人鼓舞的，并为许多进一步的研究方向铺平了道路。