A Session-Based Customer Preference Learning Method by Using the Gated Recurrent Units With Attention Function

A Session-Based Customer Preference Learning Method by Using the Gated Recurrent Units With Attention Function

In this paper, we investigate an attention function combined with the gated recurrent units (GRUs), named GRUA, to raise the accuracy of the customer preference prediction. The attention function extracts the important product features by using the time-bias parameter and the term frequency-inverse...

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Bibliographic Details
Main Authors: Jenhui Chen, Ashu Abdul
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Attention function
collaborative filtering
gated recurrent units
prediction
recommendation
Online Access:https://ieeexplore.ieee.org/document/8628957/

Internet

https://ieeexplore.ieee.org/document/8628957/

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