Selection of the optimal location for installing smart banners on campus and an automated promotional materials management equipped with recommendation system.
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1-classroom-data-EDA:
EDA of student lecture data for optimal location of smart banners -
2-classroom-data-visualization:
Analyze the optimal location for installing smart banners with visualization -
3-crawling-promotional-materials:
Collection of promotional material data from various online communities -
4-recommendation-system:
Promotional material recommendation system -
5-LSTM-material-subject-matching:
LSTM model that suggests the categories of promotional materials registered by the users -
6-app-implementation:
App implementation using React Native, Flask, and MySQL
- Foot traffic of students was identified using student classroom/classtime data
- Visualization using the Folium library
- (Recommendation System) Hybrid recommendation system based on combination of simple recommendation, content-based filtering recommendation, and collaborative filtering recommendation
- (Category Predictor) LSTM model that suggests the categories of promotional materials registered by users
