Disentangled self-attention neural network based on information sharing for click-through rate prediction

Disentangled self-attention neural network based on information sharing for click-through rate prediction

With the exponential growth of network resources, recommendation systems have become successful at combating information overload. In intelligent recommendation systems, the prediction of click-through rates (CTR) plays a crucial role. Most CTR models employ a parallel network architecture to succes...

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Bibliographic Details
Main Authors: Yingqi Wang, Huiqin Ji, Xin He, Junyang Yu, Hongyu Han, Rui Zhai, Longge Wang
Format: Article
Language:English
Published: PeerJ Inc. 2024-01-01
Series:PeerJ Computer Science
Subjects:
Feature interactions
Disentangled muti-head self-attention
Click-through rate prediction
Recommendation systems
Parallel network
Online Access:https://peerj.com/articles/cs-1764.pdf

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