In higher education, accreditation is a quality assurance process, where an
institution demonstrates a commitment to delivering high quality programs and
services to their students. For business schools nationally and internationally
the Association to Advance Collegiate Schools of Business (AACSB) accreditation
is the gold standard. For a business school to receive and subsequently
maintain accreditation, the school must undertake a rigorous, time consuming
reporting and peer review process, to demonstrate alignment with the AACSB
Standards. For this project we create a hybrid context retrieval augmented
generation pipeline that can assist in the documentation alignment and
reporting process necessary for accreditation. We implement both a vector
database and knowledge graph, as knowledge stores containing both institutional
data and AACSB Standard data. The output of the pipeline can be used by
institution stakeholders to build their accreditation report, dually grounded
by the context from the knowledge stores. To develop our knowledge graphs we
utilized both a manual construction process as well as an LLM Augmented
Knowledge Graph approach. We evaluated the pipeline using the RAGAs framework
and observed optimal performance on answer relevancy and answer correctness
metrics.

通过引入混合上下文检索增强生成流水线，该文献研究了在商学院进行认证所需的文件对齐和报告过程，使用矢量数据库和知识图构建了机构数据和 AACSB 标准数据的知识存储，并使用 RAGAs 框架评估了流水线的性能。