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Gopalan, P., Ruiz, F. J., Ranganath, R., & Blei, D. M. (2014). Bayesian Nonparametric Poisson Factorization for Recommendation Systems. In Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics (pp. 275-283).
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Reference ---------- Gopalan, P., Ruiz, F. J., Ranganath, R., & Blei, D. M. (2014). Bayesian Nonparametric Poisson Factorization for Recommendation Systems. In Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics (pp. 275-283). @inproceedings{gopalan2014bayesian, title={Bayesian Nonparametric Poisson Factorization for Recommendation Systems}, author={Gopalan, Prem and Ruiz, Francisco JR and Ranganath, Rajesh and Blei, David M}, booktitle={Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics}, pages={275--283}, year={2014} } Installation ------------ Required libraries: gsl, gslblas, pthread On Linux/Unix run ./configure make; make install ** ** Note: UNTESTED on Mac ** ** Linux is strongly recommended. On Mac, you may run into issues. If you absolutely need it to work on Mac, let me know. ** On Mac OS, the location of the required gsl, gslblas and pthread libraries may need to be specified: ./configure LDFLAGS="-L/opt/local/lib" CPPFLAGS="-I/opt/local/include" make; make install The binary 'gaprec' will be installed in /usr/local/bin unless a different prefix is provided to configure. (See INSTALL.) GAPREC: Gamma Poisson factorization based recommendation tool -------------------------------------------------------------- **gaprec** [OPTIONS] -dir <string> path to dataset directory with 3 files: train.tsv, test.tsv, validation.tsv (for examples, see example/movielens-1m) -m <int> number of items -n <int> number of users -T <int> truncation level -rfreq <int> assess convergence and compute other stats <int> number of iterations default: 10 -alpha set Gamma shape hyperparameter alpha (see paper) -C set Gamma scale hyperparameter c (see paper) -label add a tag to the output directory -gen-ranking generate ranking file to use in precision computation; see example Example -------- (1) ../src/gaprec -dir ../example/movielens -n 6040 -m 3900 -T 100 -rfreq 10 This will write output in n6040-m3900-k100-batch-alpha1.1-scale1-vb You can change the settings for the Gamma hyperparameters alpha and c (see paper) using the -alpha and the -C options. To generate the ranking file (ranking.tsv) for precision computation, run the following: (2) cd n6040-m3900-k100-batch-alpha1.1-scale1-vb ../../src/gaprec -dir ../../example/movielens -n 6040 -m 3900 -T 100 -rfreq 10 -gen-ranking This will rank all y == 0 in training and the test.tsv pairs in decreasing order of their scores, along with the non-zero ratings from test.tsv. The output is now in a new directory within the fit. Look for ranking.tsv.
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Gopalan, P., Ruiz, F. J., Ranganath, R., & Blei, D. M. (2014). Bayesian Nonparametric Poisson Factorization for Recommendation Systems. In Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics (pp. 275-283).
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