Join Research


https://ec.europa.eu/research-and-innovation/en/projects/success-stories/all/scaling-hurdles-global-science-collaboration

For students who are interested in doing research in the Recommender system (RS) areas with me, there are several steps:

  1. Read articles I wrote here: https://blog.ariflaksito.net/search/label/Recommendation%20system
  2. Search the newest papers related to the recommender system (it is about 10 - 20 papers) - you can find RS handbooks here
  3. Discuss your ideas and send those to: arif.laksito@amikom.ac.id
  4. Join the "recommender system group" at telegram: https://t.me/joinchat/CH_ihoMW7XdjZTA1

Prospective Students:

  1. Basic knowledge in Programming (Python would be better)
  2. Expected to study hard and learn new knowledge
  3. Web/Mobile Development (optional)
  4. Minimum GPA: 3.00

Available research topics:

  1. Image extraction for content-based filtering RS
  2. Music extraction recommender system
  3. Model-based recommender system in several domains
  4. Knowledge-based recommender system
  5. Cross-domain recommender system
  6. Deep learning in recommender system
  7. Aux. information & latent factors in collaborative filtering RS

Other topics:

  1. Text classification/Sentiment Analysis: RNN, LSTM, Attention, Transformer
  2. Word embedding in NLP: Glove, Word2Vec, fastText, BERT
  3. Machine learning model improvement using several datasets.
  4. Neural Machine Translation

Benefits:

  1. Free access datacamp & DQLab e-learning platform to improve your coding skills in R & Python related to Machine learning & Data Mining.
  2. Intense discussion (twice a week)
  3. Publication support (reputed journal or conference)

@datascienceinfo

Handbooks and other resources for recommender system: https://drive.google.com/drive/folders/1OXLvRDR5e_bgtVi1NwCwuB2LveJs0jHa?usp=sharing (please using Amikom mail account)

Any questions? Feel free to contact me at arif.laksito@amikom.ac.id or drop your messages to the comment form


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