Comprehensive Food Taxonomy and Classification System - Vietnam
2021 - 2023
The initial food categories in the application were inconsistent and incomplete, failing to align with customer needs and preferences. This project focused on developing a robust food taxonomy that meets business objectives and establishing a classification system capable of categorizing dishes rapidly and accurately.
Collaborate with the business team to create a food taxonomy system that aligns with business goals.
Build a rule-based NLP classifier to categorize food items into 86 categories with an average accuracy of 95%.
Develop a pipeline to automatically classify ordered dishes and user search keywords daily, providing insights into user and market behavior.
Visualize search trends by hour and geographical location to support supply-demand analysis, utilizing tools like GeoPandas and Google Data Studio.
Technologies: NLP, Machine Learning, Data Pipeline, Visualization, Geographical Analytics