Extraction and classification of indirect cost-related clauses from construction consultancy tenders with natural language processing

Date

2024-9

Author

İmamoğlu, Eray

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With the surge in demand for construction consultancy tenders, tender documents have grown in complexity, posing challenges in timely and accurate reviews. There is a significant need to help decision-makers, including tender engineers and sector professionals, identify cost-related clauses in tender documents so that precise, accurate, and comprehensive proposals can be developed. This research addresses the need to extract indirect cost-related clauses from construction consultancy tender documentation. This study uses Natural Language Processing (NLP) techniques to improve and accelerate the review process of identifying, extracting, and classifying indirect cost-related clauses from construction consultancy tenders to use them in their financial proposals. Hence, bidders can significantly reduce the time required for document analysis and double-checking if there is any missing clause. The significance of the research is for the tender review process, enabling bidders to meet stringent client deadlines while maintaining high accuracy in extracting cost-related clauses. Furthermore, the results will also contribute to the advancement of NLP applications in the consultancy domain of the construction industry.

Subject Keywords

Natural language processing, Construction Tenders, Consultancy, Indirect cost, Detecting Cost Clauses

URI

https://hdl.handle.net/11511/111407

Collections

Graduate School of Natural and Applied Sciences, Thesis