Click-through rate prediction in online advertising: A literature review
Y Yang, P Zhai - Information Processing & Management, 2022 - Elsevier
Predicting the probability that a user will click on a specific advertisement has been a
prevalent issue in online advertising, attracting much research attention in the past decades …
prevalent issue in online advertising, attracting much research attention in the past decades …
Research on disease prediction based on improved DeepFM and IoMT
Z Yu, SU Amin, M Alhussein, Z Lv - IEEE Access, 2021 - ieeexplore.ieee.org
In recent years, with the increase of computer computing power, Deep Learning has begun
to be favored. Its learning of non-linear feature combinations has played a role that …
to be favored. Its learning of non-linear feature combinations has played a role that …
JointCTR: a joint CTR prediction framework combining feature interaction and sequential behavior learning
Click-through rate (CTR) is a positive feedback of user preferences or product purchases,
and its small increase can bring huge benefits. Therefore, CTR prediction plays a key role in …
and its small increase can bring huge benefits. Therefore, CTR prediction plays a key role in …
The adverse impact of flight delays on passenger satisfaction: An innovative prediction model utilizing wide & deep learning
C Song, X Ma, C Ardizzone, J Zhuang - Journal of Air Transport …, 2024 - Elsevier
This article addresses the substantial negative influence of flight delays on passenger
satisfaction and aims to bridge the research gap in understanding passenger satisfaction …
satisfaction and aims to bridge the research gap in understanding passenger satisfaction …
Robustness and Transferability of Adversarial Attacks on Different Image Classification Neural Networks
Recent works demonstrated that imperceptible perturbations to input data, known as
adversarial examples, can mislead neural networks' output. Moreover, the same adversarial …
adversarial examples, can mislead neural networks' output. Moreover, the same adversarial …
Contextual transformer sequence-based recognition network for medical examination reports
H Wan, Z Zhong, T Li, H Zhang, J Sun - Applied Intelligence, 2023 - Springer
The automatic recognition of the medical examination report table (MERT) is receiving
increasing attention in recent years as it is an essential step for intelligent healthcare and …
increasing attention in recent years as it is an essential step for intelligent healthcare and …
A novel interest evolution network based on transformer and a gated residual for ctr prediction in display advertising
C Qin, J Xie, Q Jiang, X Chen - Neural Computing and Applications, 2023 - Springer
Efficiently extracting user interest from user behavior sequences is the key to improving the
click-through rate, and learning sophisticated feature interaction information is also critical in …
click-through rate, and learning sophisticated feature interaction information is also critical in …
TMH: Two-Tower Multi-Head Attention neural network for CTR prediction
Z An, I Joe - Plos one, 2024 - journals.plos.org
Click-through rate (CTR) prediction is a term used to predict the probability of a user clicking
on an ad or item and has become a popular research area in advertising. As the volume of …
on an ad or item and has become a popular research area in advertising. As the volume of …
Hoint: Learning explicit and implicit high-order feature interactions for click-through rate prediction
H Dong, X Wang - Neural Processing Letters, 2023 - Springer
Click-through rate (CTR) prediction is a research hotspot in the field of recommendation
systems and online advertising. Because of the diversity, large-scale, and high real-time …
systems and online advertising. Because of the diversity, large-scale, and high real-time …
Knowledge-aware recommendation model with dynamic co-attention and attribute regularize
G Yin, F Chen, Y Dong, G Li - Applied Intelligence, 2022 - Springer
As important information provided by recommender systems, knowledge graphs are widely
applied in computer science and many other fields. The recommender system performance …
applied in computer science and many other fields. The recommender system performance …