This is a class project developed for a course from Simon Fraser University's master of professional computer science program. Like the original Movie Lens system developed by a research lab in the Department of Computer Science and Engineering at the University of Minnesota, this is a personalized recommender system aiming to deliver good UX when navigating through a large repository of contents (movies/videos).
- The scale of the content repository: 10^6.
- The number of active users in the system: 10^7.
- Must achieve high precision.
- Under resonable cost, 95th percentile latency should be kept below 1 second.
- https://grouplens.org/datasets/movielens/latest
- https://towardsdatascience.com/movie-recommendation-system-based-on-movielens-ef0df580cd0e
- This product uses the TMDB API but is not endorsed or certified by TMDB.
- third_party/README.md
- src/ingestion/README.md
- src/loader/README.md
- src/feature_processor/README.md
- src/model/README.md
- DaviesX (Chifeng Wen) -> cwa258 (chifeng_wen@sfu.ca)
- ffmm6521 (Min Fei) -> mfa94 (??@sfu.ca)
- greedcat (Mingyi Wu) -> mingyiwu (mingyiwu@sfu.ca)