Incorporating Natural Language Processing models in Mexico City's 311 Locatel

Alejandro Molina-Villegas, Edwin Aldana-Bibadilla,Oscar Siordia, Jorge Perez

LatinX in AI at North American Chapter of the Association for Computational Linguistics Conference 2022(2022)

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摘要
Natural Language Processing based technologies are transforming various sectors by facilitating new ways of providing services through Artificial Intelligence (AI). In this paper, we describe the methodology and present the challenges encountered during the creation of a Deep Learning-based model for classifying citizen service requests. Our system is able to effectively recognize among 48 categories of public services with an accuracy of 97% and was integrated into Mexico City’s 311, significantly increasing the government’s ability to provide better services.
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