Natural Language Processing (NLP)-Driven Classification of Pre-Bid Request for Information (RFI)
Rabin Shrestha, Taewoo Ko, JeeHee Lee · 2024
Poor quality of bid documents impacts bidders’ cost estimates and bid price, and further leads to claims/dispute during the project implementation. As the problems and ambiguities in the bid documents are addressed by the pre-bid request for information (RFI), pre-bid RFI analysis helps determine major ambiguities in the bid documents that should be clarified for enhancing bid documents’ quality. This study uses pre-bid RFI as the principal data for obtaining good quality bid documents. Natural language processing (NLP) is used to pre-process/transform unstructured raw text data, and machine learning-driven classifier is applied for the classification of collected pre-bid RFI. The proposed method can automatically identify the critical pre-bid RFI that can lead to significant revision in the original bid documents. This study can contribute to efficient pre-bid RFI management that facilitates bidding process and can improve bid document quality for similar projects to be carried out in the future.