TY - GEN
T1 - Semi-sparse algorithm based on multi-layer optimization for recommendation system
AU - Guan, Hu
AU - Li, Huakang
AU - Guo, Minyi
PY - 2012
Y1 - 2012
N2 - Collaborative filter (CF) is the most successful technique in recommender system, which makes personalize recommendations during online interaction. We propose a new Semi-sparse algorithm based on multi-layer optimization to speed up the basic Pearson Correlation Coefficient of CF. Semi-sparse algorithm spares out over-reduplicate accessing and judgement on selected sparse vector to accelerate the batch of similarity-comparisons in one thread. We propose a reduce-vector in thread-pool to restrict the lock using on critical resources in parallelize implementation. Thread-pool is wrapped with Pthreads on multi-core node to make semi-sparse parallelization more easily. A shared zip file is read to cut down messages with Message Passing Interface package. The performance of proposed semi-sparse with multi-layer framework achieved a brilliant speedup in the evaluation of Netflix, MovieLens and MovieLen1600.
AB - Collaborative filter (CF) is the most successful technique in recommender system, which makes personalize recommendations during online interaction. We propose a new Semi-sparse algorithm based on multi-layer optimization to speed up the basic Pearson Correlation Coefficient of CF. Semi-sparse algorithm spares out over-reduplicate accessing and judgement on selected sparse vector to accelerate the batch of similarity-comparisons in one thread. We propose a reduce-vector in thread-pool to restrict the lock using on critical resources in parallelize implementation. Thread-pool is wrapped with Pthreads on multi-core node to make semi-sparse parallelization more easily. A shared zip file is read to cut down messages with Message Passing Interface package. The performance of proposed semi-sparse with multi-layer framework achieved a brilliant speedup in the evaluation of Netflix, MovieLens and MovieLen1600.
KW - message passing interface
KW - recommendation system
KW - reduce vector
KW - semi-sparse algorithm
KW - thread pool
UR - http://www.scopus.com/inward/record.url?scp=84863376181&partnerID=8YFLogxK
U2 - 10.1145/2141702.2141719
DO - 10.1145/2141702.2141719
M3 - Conference Proceeding
AN - SCOPUS:84863376181
SN - 9781450312110
T3 - Proceedings of the 2012 International Workshop on Programming Models and Applications for Multicores and Manycores, PMAM 2012
SP - 148
EP - 155
BT - Proceedings of the 2012 International Workshop on Programming Models and Applications for Multicores and Manycores, PMAM 2012
T2 - 2012 International Workshop on Programming Models and Applications for Multicores and Manycores, PMAM 2012
Y2 - 26 February 2012 through 26 February 2012
ER -