Natural Language Processing Model for Managing Maintenance Requests in Buildings
Autor(en): |
Yassine Bouabdallaoui
Zoubeir Lafhaj Pascal Yim Laure Ducoulombier Belkacem Bennadji |
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Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | Buildings, 19 August 2020, n. 9, v. 10 |
Seite(n): | 160 |
DOI: | 10.3390/buildings10090160 |
Abstrakt: |
In recent years, facility management (FM) has adopted many computer technology solutions for building maintenance, such as building information modelling (BIM) and computerized maintenance management systems (CMMS). However, maintenance requests management in buildings remains a manual and a time-consuming process that depends on human management. In this paper, a machine-learning algorithm based on natural language processing (NLP) is proposed to classify maintenance requests. This algorithm aims to assist the FM teams in managing day-to-day maintenance activities. A healthcare facility is addressed as a case study in this work. Ten-year maintenance records from the facility contributed to the design and development of the algorithm. Multiple NLP methods were used in this study, and the results reveal that the NLP model can classify work requests with an average accuracy of 78%. Furthermore, NLP methods have proven to be effective for managing unstructured text data. |
Copyright: | © 2020 by the authors; licensee MDPI, Basel, Switzerland. |
Lizenz: | Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden. |
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11.09.2020 - Geändert am:
02.06.2021