解释性情绪归因、生成与再分类的常识推理框架
A Commonsense Reasoning Framework for Explanatory Emotion Attribution, Generation and Re-classification
摘要：
DEGARI（Dynamic Emotion Generator And Reclassifier）是一个可解释的情感归因和推荐系统。该系统依赖于最近推出的常识推理框架，TCL逻辑，这是基于一个人性化的过程中的描述逻辑知识库的新概念的自动生成。从基于Plutchik模型的情感的本体形式化开始，称为Arsartica，该系统利用逻辑TCL来自动生成复合情感的新颖常识语义表示（例如，根据Plutchik，从Joy和Trust的组合中导出的Love）。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RaiPlay中的编辑内容，RaiPlay是意大利广播公司的在线平台。我们展示了报告的结果（根据获得的重新分类，分配给这种重新分类的用户评级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。
英文摘要：
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 TCL 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 TCL 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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
