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hidasib / GRU4Rec

GRU4Rec is the original Theano implementation of the algorithm in "Session-based Recommendations with Recurrent Neural Networks" paper, published at ICLR 2016 and its follow-up "Recurrent Neural Networks with Top-k Gains for Session-based Recommendations". The code is optimized for execution on the GPU.
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clickstream session classification #13

Closed polya20 closed 4 years ago

polya20 commented 6 years ago

So I have the data in the following form, I use char-rnn/word-rnn to predict the next click and classify if the user will convert or not. The question is what changes need to be made to incorporate to classify if a user given the user cicks is going to buy or defer. A quick rough brain dump is sufficient.

Session1,P19,P69,P71,P72,P24,Buy Session2,P0,P6,P14,P10,P18,P32,P50,Defer Session3,P7,P0,P26,P6,P33,Defer Session4,P10,P6,P11,P12,Defer Session5,P2,P10,P18,P32,Defer Session6,P0,P10,P18,P32,P50,P37,P7,Buy Session7,P10,P18,P32,P50,P37,Buy Session8,P0,P33,P40,P7,P10,P18,Defer Session9,P10,P18,P7,P0,P6,P33,P14,P5,P68,P32,P50,P37,Buy Session10,P10,P7,P0,P18,P32,Defer Session11,P10,P18,P32,P50,P37,Buy Session12,P11,P7,P0,P10,P18,Defer Session13,P0,P3,P39,P30,P26,P7,P36,P20,Defer Session14,P0,P10,P18,P32,P50,P37,Buy Session15,P6,P28,P26,P7,P8,Defer Session16,P10,P7,P26,P5,P68,P82,P84,P37,Buy Session17,P10,P18,P32,P50,P37,Buy Session18,P7,P23,P34,P35,P37,Buy
hidasib commented 4 years ago

This question is not related to this repo. But if you want to do classification, you can use the session representation (e.g. last value of the hidden state, combined value of hidden states with attention, etc) as an input of the classifier.