Metadata Extraction of RFIs Using Natural Language Processing and Machine Learning Algorithms

Abstract: Assigning metadata of RFIs accurately plays an important role in the management of RFI documents. However, these metadata are manually entered in the RFI management system, which results in loss of time and incorrect entries. This study aims to demonstrate that metadata of RFI documents can be obtained and assigned automatically using NLP and ML algorithms. The results show that ML models perform well in automatically extracting the metadata of RFIs. The findings of this study can be used to develop an AI based RFI management system by integrating NLP and ML models into the system.