Data Mining meets Recommender Systems

Main objectives

Use data mining techniques (i.e. clustering methods) to extract useful information from a large dataset (40 million rows) of user events in a social network. The dataset will require many pre-processing steps. The objective is to use those extracted features and information in a recommender system.

Both the dataset and the company's name will remain undisclosed.

Context

This project is developed in Python 3 for the Hands-on Recommender Systems seminar of the Master in Computer Science in the university of Fribourg, Switzerland.

This seminar is worth 5 ECTS points.

Fall 2020.

Project supervisor: Dr. Luis Terán

Team members

• Chacun Guillaume
• Vorpe Fabien