kimanh358/HUPH_decision_policy_nutrition

AI Summary: The task involves updating a conceptual model for analyzing the impact of school nutrition policies in Hanoi. This update requires replacing a binary presence/absence analysis with a more sophisticated Term Frequency-Inverse Document Frequency (TF-IDF) analysis using R libraries `tidytext` and `dplyr` to create a document-term matrix with TF-IDF weights. The goal is to improve the model's accuracy and insights by considering the frequency and importance of terms within the collected literature.