Comments (3)
I'll put up a license, but it is a work in progress. I hope we can get to it in the next few weeks. (I'll also publish a considerable speed-up update along with the license.)
The basic idea for the license is that the code is free to use for research (publications should cite the two papers describing this algorithm), but the derivative code can't be sold or used in commercial systems. For use in commercial systems you'll need to ask for a separate license.
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@hidasib, thanks for the fast response. I understand your hesitance of putting your code under MIT which would also allow commercial use of your work. There are already reimplementations of your code like here which also lack a proper license statement.
I wonder if you are already earning money by selling commercial licenses since a clean-room implementation, only based on your paper, would also be a legal way to commercially use the GRU4Rec method without such a commercial license. So my actual point is, wouldn't it be easier for everyone involved to distribute under MIT/BSD/Apache2 as many great open source projects like Scikit-Learn, LightFM, Pandas etc. do in the spirit of sharing?
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License was added earlier this year, closing issue.
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Related Issues (20)
- About training time HOT 1
- Is it possible to output the embedding of user/session and item vectors? HOT 1
- NOT RNN MODEL HOT 2
- Additional Negative Sampling: Conditional Statement Logic Error HOT 1
- generate_samples function call in gru4rec.py HOT 2
- BPR loss implementation question
- Fit function in gru4rec.py missing data sort HOT 1
- predict_next_batch not considering other products in the same session HOT 2
- (Question) - How to use all items in a session for prediction? HOT 2
- No hidden state reset in get_metrics HOT 4
- Where is the data file ?
- theano error HOT 2
- Can you make a brief explaination on how you calculate recall ? HOT 2
- Incremental training (retrain) support removed
- ValueError: Input dimension mis-match. (input[2].shape[0] = 2080, input[3].shape[0] = 32)
- cuda error
- GFF code
- Testing Error:: start = offset_sessions[iters] IndexError: index 2 is out of bounds for axis 0 with size 2
- Evaluating baselines
- Non-session based custom dataset HOT 2
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