Build your own recommendation engine with Neo4j

https://slides.com/saidbouig/neo4j-recommendation-engine-devoxxma#/

Clone project

git clone https://github.com/saidbouig/neo4j_recommendation_engine_devoxx

Setup Python environment / install packages

you need Python and pip installed

virtualenv env
source ./env/bin/activate
pip install -r requirements.txt

Run Neo4j container

you need docker and docker-compose installed

docker-compose up

Get TMDB https://www.themoviedb.org/ API key and replace it in constants.py

KEY='YOUR_API_KEY'

Run movie_ingestor.py to get movies from tmdb

python movie_ingestor.py

Get User ratings from Movielens Dataset

Goto

localhost:7474/browser/

Then copy this query to import ratings

LOAD CSV FROM 'https://gist.githubusercontent.mirror.nvdadr.com/saidbouig/9bbe7b22730fe93f19ca254df93de503/raw/3bdd87939401151f7a1aab133f83bcbf542f5782/user_ratings.edges' AS row

WITH toInteger(row[0]) AS userId, toInteger(row[1]) AS movieId, toFloat(row[2]) AS rating, toInteger(row[3]) AS timeStamp

MATCH(m: Movie {id: movieId})
MERGE(u: User {id: userId})

MERGE(u)-[rel:RATED {rating: rating, timeStamp: timeStamp}] -> (m)
RETURN count(rel)

Useful links

Cypher langauge documentaion

https://neo4j.com/docs/cypher-manual/current/

TMDB API KEY

https://www.themoviedb.org/settings/api

TMDB API documentation

https://developers.themoviedb.org/3/getting-started/introduction