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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Research on CTR prediction based on stacked autoencoder
Qianqian Wang, Liu Fang-ai, Shuning Xing, et al.
Applied Intelligence (2019) Vol. 49, Iss. 8, pp. 2970-2981
Closed Access | Times Cited: 12

Showing 12 citing articles:

Click-through rate prediction in online advertising: A literature review
Yanwu Yang, Panyu Zhai
Information Processing & Management (2022) Vol. 59, Iss. 2, pp. 102853-102853
Open Access | Times Cited: 67
Generative Adversarial Networks in Medical Image Processing
Meiqin Gong, Siyu Chen, Qingyuan Chen, et al.
Current Pharmaceutical Design (2020) Vol. 27, Iss. 15, pp. 1856-1868
Closed Access | Times Cited: 45
Broad learning system for semi-supervised learning
Zheng Liu, Shiluo Huang, Wei Jin, et al.
Neurocomputing (2021) Vol. 444, pp. 38-47
Closed Access | Times Cited: 27
Click-Through Rate Prediction in Online Advertising: A Literature Review
Yanwu Yang, Panyu Zhai
SSRN Electronic Journal (2022)
Open Access | Times Cited: 7
XGBDeepFM for CTR Predictions in Mobile Advertising Benefits from Ad Context
Han An, Jifan Ren
Mathematical Problems in Engineering (2020) Vol. 2020, pp. 1-7
Open Access | Times Cited: 9
A novel interest evolution network based on transformer and a gated residual for CTR prediction in display advertising
Chaoyong Qin, Jialin Xie, Qiuxian Jiang, et al.
Neural Computing and Applications (2023) Vol. 35, Iss. 35, pp. 24665-24680
Closed Access | Times Cited: 2
Hierarchical attention and feature projection for click-through rate prediction
Jinjin Zhang, Chengliang Zhong, Shouxiang Fan, et al.
Applied Intelligence (2021) Vol. 52, Iss. 8, pp. 8651-8663
Closed Access | Times Cited: 4
Rational satisficing heuristics as determinants of online search behavior
Debora Di Caprio, Francisco J. Santos‐Arteaga
International Journal of Information Management Data Insights (2024) Vol. 4, Iss. 1, pp. 100229-100229
Open Access
CFF: combining interactive features and user interest features for click-through rate prediction
Lin Zhang, Liu Fang-ai, Hongchen Wu, et al.
The Journal of Supercomputing (2023) Vol. 80, Iss. 3, pp. 3282-3309
Closed Access | Times Cited: 1
A new algorithm for modeling online search behavior and studying ranking reliability variations
Debora Di Caprio, Francisco J. Santos‐Arteaga, Madjid Tavana
Applied Intelligence (2021) Vol. 52, Iss. 7, pp. 7529-7549
Closed Access | Times Cited: 3
Se-xDeepFEFM: Combining Low-Order Feature Refinement and Interaction Intensity Evaluation for Click-Through Rate Prediction
Guangli Li, Guangxin Xu, Guangting Wu, et al.
Symmetry (2022) Vol. 14, Iss. 10, pp. 2123-2123
Open Access | Times Cited: 1
Research on Improvement of the Click-Through Rate Prediction Model Based on Differential Privacy
Lei Tian, Lina Ge, Zhe Wang, et al.
IEEE Access (2022) Vol. 10, pp. 110960-110969
Open Access
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