Tackling the Data Sourcing Problem in Construction Procurement Using File-Scraping Algorithms-Reference-Cited by-同舟云学术

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Tackling the Data Sourcing Problem in Construction Procurement Using File-Scraping Algorithms

Published:2023-10-24 Issue: Volume: Page:
ISSN:
Container-title:The 1st International Online Conference on Buildings
language:
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Author:

Jacques de Sousa Luís¹²³^ORCID,Poças Martins João¹²³^ORCID,Sanhudo Luís²³^ORCID

Affiliation:

1. Department of Civil Engineering (DEC), Faculty of Engineering of the University of Porto (FEUP), 4200-465 Porto, Portugal

2. CONSTRUCT/GEQUALTEC, FEUP–DEC, 4200-465 Porto, Portugal

3. BUILT CoLAB–Collaborative Laboratory for the Future Built Environment, 4150-003 Porto, Portugal

Publisher

MDPI

Link

https://www.mdpi.com/2673-4591/53/1/34/pdf

Reference19 articles.

1. Comparing natural language processing (NLP) applications in construction and computer science using preferred reporting items for systematic reviews (PRISMA);Chung;Autom. Constr.,2023

2. Jacques de Sousa, L., Poças Martins, J., Santos Baptista, J., and Sanhudo, L. (2022, January 7–9). Towards the Development of a Budget Categorisation Machine Learning Tool: A Review. Proceedings of the Trends on Construction in the Digital Era, Guimarães, Portugal.

3. Sepasgozar, S.M.E., and Davis, S. (2018). Construction Technology Adoption Cube: An Investigation on Process, Factors, Barriers, Drivers and Decision Makers Using NVivo and AHP Analysis. Buildings, 8.

4. Munawar, H.S., Ullah, F., Qayyum, S., and Shahzad, D. (2022). Big Data in Construction: Current Applications and Future Opportunities. Big Data Cogn. Comput., 6.

5. Data on Field Canals Improvement Projects for Cost Prediction Using Artificial Intelligence;Elmousalami;Data Brief,2020

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