a fast and lightweight collaborative filtering algorithm for binary ratings.
If you use LCBM please cite the following paper:
- F. Petroni, L. Querzoni, R. Beraldi, M. Paolucci: "LCBM: Statistics-Based Parallel Collaborative Filtering." In: Proceedings of the 17th International Conference on Business Information Systems (BIS), 2014.
###Hadoop MapReduce:
To run the project on hadoop type the following:
bin/hadoop jar /home/hduser/LCBM_mapreduce.jar train test [options]
Parameters:
-
train
: the name of the file with the train data -
test
: the name of the file with the test data.
Options:
-
-k int
-> specifies the multiplicative factor for the SE. Default 2. -
-split_token char
-> specifies the character that splits the dataset. -
-output1 string
-> specifies the name of the first output directory in the hdfs. -
-output2 sting
-> specifies the name of the second output directory in the hdfs.
bin/hadoop jar /home/hduser/LCBM_mapreduce.jar ml100k/trace1.base ml100k/trace1.test