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Thesis topics Recommender Systems 2019-2020

  • Beating the stock market: data analysis for predicting future share prices.
  • Design and development of a Health Recommender Systems
  • Design of a recommender systems that is robust for attacks by malicious users
  • Detecting relevant context parameters and incorporating these into a recommender system
  • Drive lane detection using accelerometer and GPS signal
  • Improve your badminton skills based on localization and motion tracking
  • Indoor soccer player performance analysis based on location, heart rate and activity monitoring
  • Location estimation exploiting sensor data of mobile device and pattern recognition
  • Machine Learning Versus Classic Recommenders
  • Multi-objective optimization using evolutionary algorithms in production scheduling for intelligent manufacturing
  • Music recommendation using genetic programming
  • Recommending healthy recipes for groups of users.
  • Using Machine Learning for Improving Indoor Positioning
  • Using wearables for innovative human-computer interaction

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