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GETFLIC |
Not Netflix... a movie recommendation system |
asmitks/GETFLIX |
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This is a 🎥 movie recommendation system based on collaborative learning (user-user and item-item) which was applied on the IMDB database.The recommendation system asks for ratings on 4 or more movies out of approx. 500 movies and returns 4 recommendations each for User-User and Item-Item collaborative learning algorithms.
- Python 3.5
- Mongo DB
- Docker
- Heroku
- mlab
- PyMongo
- Flask
- HTML/CSS
- Pandas
- Beautiful soup
- Collective Intelligence by Toby Segaran
You can find the hosted app here GETFLIX
At the above link you will see a page with approx. 500 movies.You need to rate any 4(k) or more movies and press submit at the bottom of the page to get your recommendations
you can rate the movies by moving the slider thumb to 5 possible positions from (1 to 5) initially all sliders are at 0th position
You will be presented 4 recommendations each of user-user and item-item collaborative learning.
It is possible that user-user algo doesn't return 4 movies due to its dependency on the data of user ratings.
for explanation behind the algos and a brief report refer to Report.pdf
Brief description of folder/files in the repo.
The main python3 flask file that contains the main algorithms and logic
python3 app.py
Main template that is returned as the home page
Template that is returned when both algos return answers
Template is returned when user-user algo does not return answer.
contains the css file style.css
It contains all raw data taken from movie lense.
Used for creating mongo db database after data cleaning
python3 other/mongs.py
Used for scraping thumbnails from dedicated sites of imdb
python3 other/scrape.py
Used for printing required tags that need to be inserted into HTML file.
bash python3 other/change.py
Used to run using docker commands to run using docker To run the dockerfile:
docker build -t flask-getflix:latest .
To run the app:
docker run flask-getflix
The mongoDB collections that I used can be accessed thorough
MONGODB_URI='mongodb://asmit:[email protected]:43062/imdb'
MONGODB_URI='mongodb://asmit:[email protected]:27825/data_imdb'