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Please advice, am I thinking correctly: is it possible to represent customer behavior data from an online store as a sequence data? Because it is describing interactions of the customer with the shop through time.

So in this case N would be the number of users (or number of user sessions), T / time window I could set myself and D I could set also myself taking only event type (purchase, view, etc.) or something else like price, brand etc.(please see screenshot below) enter image description here

Please share your opinion Many thanks in advance

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Definitely, it is a good idea and has been attempted before. Have a look at Alibaba's paper which uses transformers: https://www.kdnuggets.com/2019/08/order-matters-alibabas-transformer-based-recommender-system.html

https://arxiv.org/abs/1905.06874

There are also various other papers that use other types of seq2seq for recommender systems.

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  • $\begingroup$ thank you for links! $\endgroup$ Dec 5 '20 at 16:57
  • $\begingroup$ in this case, if I have have only e.g. 16 features, than my model dimension (d_model) will be 16...is it even possible? In the attention paper they have 512... $\endgroup$ Jan 19 at 12:18

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