Natural Language Processing (NLP)-Driven Classification of Pre-Bid Request for Information (RFI)
Publication: Computing in Civil Engineering 2023
ABSTRACT
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.
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Published In
Computing in Civil Engineering 2023
Pages: 59 - 66
History
Published online: Jan 25, 2024
ASCE Technical Topics:
- Artificial intelligence and machine learning
- Automatic identification systems
- Bids
- Business management
- Computer programming
- Computing in civil engineering
- Construction costs
- Construction engineering
- Construction management
- Contracts and subcontracts
- Data collection
- Detection methods
- Engineering fundamentals
- Equipment and machinery
- Methodology (by type)
- Practice and Profession
- Pricing
- Project management
- Research methods (by type)
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