README.md

RecommenderItemCF

Recommender System based on item collaborative filtering running on Hadoop

This is a chain of five map-reduce jobs.

Input sample:
user_id, movie_id, rating
1488844,45,3
822109,55,5
885013,1,4
30878,12,4
823519,22,3
893988,66,3
124105,8,4
1248029,7,3
1842128,21,4
2238063,13,3
1503895,44,4
2207774,7,5
2590061,2,3
2442,6,3
….

Map-reduce job 1: Divide data by user_id

Input:
rows of user_id, movie_id, rating
Output:
user_id1\t< movie_A:rating, movie_B:rating, …>
user_id2\t< movie_B:rating, movie_C:rating, …>
user_id3\t< movie_A:rating, movie_C:rating, …>
…

Map-reduce job2: Build Co-occurrence Matrix

Input:
rows of user_id \t movie_A:rating, movie_B:rating, movie_C:rating, …
Output:
movie_A:movie_B \t relation (number of co-occurrences)
movie_A:movie_C \t relation
movie_B:movie_C \t relation
…

Map-reduce job 3: Normalize co-occurrence matrix

Input:
rows of movie_id:movie_id \t relation
Output:
movie_A \t movie_B=relation_normed
movie_A \t movie_C=relation_normed
movie_B \t movie_C=relation_normed
…

Map-reduce job 4: Multiply normalized co-occurrence matrix and rating matrix

Mapper 1 input:
rows of moive_id \t moive_id=relation_normed
Mapper 2 input:
rows of user_id, movie_id, rating
Output:
user_id1:movie_A \t rating_partial
user_id2:movie_A \t rating_partial
user_id1:movie_B \t rating_partial
user_id1:movie_A \t rating_partial
user_id2:movie_C \t rating_partial
user_id2:movie_A \t rating_partial
…

Map-reduce job 5: Sum up partial ratings

Input:
rows of user_id:movie_id \t rating_partial
Output:
user_id1:movie_A \t rating
user_id1:movie_B \t rating
user_id1:movie_C \t rating
user_id2:movie_A \t rating
user_id2:movie_B \t rating …

Run

hdfs dfs -mkdir /input
hdfs dfs -put input/* /input
hadoop com.sun.tools.javac.Main *.java
jar cf recommender.jar .class
hadoop jar recommender.jar Driver /input /dataDividedByUser /coOccurrenceMatrix /normalize /multiplication /sum
hdfs dfs -cat /sum/
// args0: original input directory
// args1 – args5: output directories for map-reduce jobs 1-5

Maven version

https://github.com/fanchi/RecommenderItemCFMaven