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This graph maps the connections between all the collaborators of {}'s publications listed on this page.
Each link represents a collaboration on the same publication. The thickness of the link represents the number of collaborations.
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A word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Cadavid, J. P. U., Lamouri, S., Grabot, B., Pellerin, R., & Fortin, A. (2019, September). Estimation of production inhibition time using data mining to improve production planning and control [Paper]. International Conference on Industrial Engineering and Systems Management (IESM 2019), Shanghai, China (6 pages). External link
Danjou, C., Le Duigou, J., & Eynard, B. (2014, September). OntoSTEP-NC for information feedbacks for CNC to CAS/CAM systems [Paper]. IFIP International Conference on Advanced Production Management Systems (APMS 2014), Ajaccio, France. External link
Grabot, B. (1993). Systèmes de transport d'atelier : caractérisation des modes de marche nominal et dégradés. (Technical Report n° EPM-RT-93-20). Restricted access
Nguyen, A., Usuga-Cadavid, J. P., Lamouri, S., Grabot, B., & Pellerin, R. (2020, October). Understanding Data-Related Concepts in Smart Manufacturing and Supply Chain Through Text Mining [Paper]. 10th International Workshop on Service Oriented, Holonic and Multi-agent Manufacturing Systems for Industry of the Future (SOHOMA 2020), Paris, France. External link
Ouzineb, M., Mhada, F.-Z., Pellerin, R., & El Hallaoui, I. (2014, September). A Hybrid Method for Solving Buffer Sizing and Inspection Stations Allocation [Paper]. IFIP International Conference on Advances in Production Management Systems (APMS 2014), Ajaccio, France. External link
Usuga Cadavid, J. P., Lamouri, S., Grabot, B., Pellerin, R., & Fortin, A. (2020). Machine learning applied in production planning and control: a state-of-the-art in the era of industry 4.0. Journal of Intelligent Manufacturing, 31(6), 1531-1558. External link
Usuga Cadavid, J. P., Grabot, B., Lamouri, S., Pellerin, R., & Fortin, A. (2020). Valuing free-form text data from maintenance logs through transfer learning with CamemBERT. Enterprise Information Systems, 16(6), 29 pages. External link