neo4j_recommender_jaccard.py

neo4j_recommender_jaccard.py

%%time
def get_recommendations_jaccard(user_id):
    # Based on the code in https://neo4j.com/docs/graph-data-science/current/alpha-algorithms/jaccard/
    query = f"""
    MATCH (u1:User)-[:BOOKMARKED]->(song1)
    WITH u1, collect(id(song1)) AS u1Song
    WHERE u1.id = '{user_id}'
    MATCH (u2:User)-[:BOOKMARKED]->(song2) WHERE u1 <> u2
    WITH u1, u1Song, u2, collect(id(song2)) AS u2Song
    RETURN u2.id AS user_id,
           gds.alpha.similarity.jaccard(u1Song, u2Song) AS similarity
    ORDER BY user_id, similarity DESC
    """
    with driver.session() as session:
        result = session.run(query)
    df_recommendations = pd.DataFrame([r for r in result.values()])
    df_recommendations.columns = ['user_id', 'similarity']
    df_recommendations = df_recommendations[df_recommendations['similarity'] > 0]
    df_recommendations.sort_values(['similarity'], ascending = False, inplace = True)
    
    return df_recommendations['user_id'].tolist()
    
recommendations = get_recommendations_jaccard('jeanmidev')