Electronic medical records imputation by temporal Generative Adversarial Network
Y Yin, Z Yuan, IM Tanvir, X Bao - BioData Mining, 2024 - Springer
The loss of electronic medical records has seriously affected the practical application of
biomedical data. Therefore, it is a meaningful research effort to effectively fill these lost data …
biomedical data. Therefore, it is a meaningful research effort to effectively fill these lost data …
TIEN: Temporal interest-aware evolution model for “Next Item Recommendation”
Y Yin, J Wang, HA Barua, X Bao - Expert Systems with Applications, 2024 - Elsevier
The “next item recommendation” is used to predict the next item that a user may be
interested in and its main challenges is identifying the user's interests. The current state-of …
interested in and its main challenges is identifying the user's interests. The current state-of …
Deep user and item inter-matching network for CTR prediction
Z Yuan, Y **ao, P Yang, Q Hao, H Wang - International Conference on …, 2023 - Springer
CTR prediction plays an important role in increasing company revenue and user
experience, and many efforts start with historical behavior to uncover user interest. There are …
experience, and many efforts start with historical behavior to uncover user interest. There are …
Attention-Based Feature Interaction Deep Factorization Machine for CTR Prediction
P Yang, Y Han, Y **ao, W Zheng - International Conference on Artificial …, 2023 - Springer
Abstract Click-Through Rate (CTR) prediction is widely used in many fields, such as web
search, recommender systems, etc. Recently, the CTR prediction model using deep learning …
search, recommender systems, etc. Recently, the CTR prediction model using deep learning …
Session Interest Model for CTR Prediction Based on Feature Co-Action Network
Q Wang, X Zhao, Q Tan - 2024 - researchsquare.com
The main purpose of click-prediction models is to predict the probability of customers
clicking on products and provide support for advertising decisions of businesses. However …
clicking on products and provide support for advertising decisions of businesses. However …
Feature Representation Enhancing by Context Sensitive Information in CTR Prediction
H Liu, Y Guo, L Wang, X Song - International Conference on Advanced …, 2023 - Springer
Abstract Click-Through-Rate (CTR) is a fundamental metric used to assess the efficacy of
recommendation systems. In the past, most CTR prediction approaches focused on …
recommendation systems. In the past, most CTR prediction approaches focused on …