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This is a Java-based benchmark for matrix approximation based collaborative filtering

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StableMA

[Read Me]

This code implemented:

  1. Regularized SVD. Arkadiusz Paterek. Improving regularized singular value decompositionfor collaborativefiltering. In KDD CUP, 2007.
  2. Group Sparsity Matrix Factorization. Ting Yuan, Jian Cheng, Xi Zhang, Shuang Qiu, Hanqing Lu. Recommendation by mining multiple user behaviors with group sparsity. In AAAI, 2014.
  3. Stable Matrix Approximation. Dongsheng Li, Chao Chen, Qin Lv, Junchi Yan, Li Shang, Stephen Chu. Low-Rank Matrix Approximation with Stability. In ICML, 2016.
  4. WEMAREC. Chao Chen, Dongsheng Li, Yingying Zhao, Qin Lv, Li Shang. WEMAREC: Accurate and Scalable Recommendation through Weighted and Ensemble Matrix Approximation. In SIGIR, 2015.

[Import Guidance]

Please use the lastest Eclipse Mar to import this project, and note that the dependencies are managed by Maven Plug-in. Therefore, if you had dependency issues, please use Maven to import this project again.

[Running Suggestion]

  1. We upload a workable MovieLens-10M and 20M data-set, which can be downloaded from ML-10M or ML-20M.
  2. If you upzip one dataset in the path "C:/Dataset/", please set the variable "$ROOT_DIR_ARR=C:/Dataset/1/" in the config file under folder "src/main/resources/samples".
  3. Run the test cases under folder "src/test/java".

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