In this research, we develop a taxonomy to conceptualize a comprehensive overview of the constituting characteristics that define retrieval augmented generation (RAG) applications, facilitating the adoption of this technology for different application domains. To the best of our knowledge, no holistic RAG application taxonomies have been developed so far. We employ the method foreign to ACL and thus contribute to the set of methods in the taxonomy creation. It comprises four iterative phases designed to refine and enhance our understanding and presentation of RAG's core dimensions. We have developed a total of five meta-dimensions and sixteen dimensions to comprehensively capture the concept of RAG applications. Thus, the taxonomy can be used to better understand RAG applications and to derive design knowledge for future solutions in specific application domains.

翻译：本研究构建了一个分类体系，旨在系统化地概念化定义检索增强生成（RAG）应用的构成特征，从而促进该技术在不同应用领域的采纳。据我们所知，目前尚未有完整的RAG应用分类体系被提出。我们采用了不同于ACL领域常规的方法，从而为分类体系的构建方法集合做出了贡献。该体系包含四个迭代阶段，旨在深化和完善我们对RAG核心维度的理解与呈现。我们共提出了五个元维度和十六个维度，以全面捕捉RAG应用的概念内涵。因此，该分类体系可用于更好地理解RAG应用，并为特定应用领域未来解决方案的设计提供知识基础。