Comments for https://medium.com/47billion/recommendation-system-using-graph-database-9f9fbca71a53

movies.cypher

//Movies based on similar users and favorite genres

MATCH (u:Users)-[:WATCHED]->(m:Movies) 
WHERE u.userId ='1' 
WITH collect(m) as watchedMovies

MATCH (u:Users)-[:WATCHED]->(m1:Movies)-[s:SIMILAR]->(m2:Movies), 
      (m2)-[:GENRES]->(g:Genres), (u)-[:FAVORITE]->(g) 
WHERE u.userId ='10' and m2 IN watchedMovies 
RETURN distinct u.userId as userId, g.genres as genres, m2.title as title, m2.rating_mean as rating 
ORDER BY m2.rating_mean DESC LIMIT 10;


// Item-Item Similarity 

MATCH (m2:Movies {movieId: "10"})-[:GENRES]->(g:Genres)<-[:GENRES]-(other:Movies) 
WITH m2, other, COUNT(g) AS intersection, COLLECT(distinct g.genres) AS genres 

MATCH (m2)-[:GENRES]->(m2g:Genres) 
WITH m2,other, intersection,genres, COLLECT(m2g.genres) AS s1 


MATCH (other)-[:GENRES]->(og:Genres) 
WITH m2,other,intersection,genres, s1, COLLECT(og.genres) AS s2 

WITH m2,other,intersection,s1,s2 
WITH m2,other,intersection,s1+[x IN s2 WHERE NOT x IN s1] AS union, s1, s2
// ... missing bits here ...