Deep Dynamic Interest Learning With Session Local and Global Consistency for Click-Through Rate Predictions
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2020.3036164
Abstract: Click-through rate (CTR) prediction is the core task in an online advertising system. How to capture the users’ dynamic interests through the behavior sequences to predict CTR is a challenging problem in the real-world applications.… read more here.
Keywords: dynamic interest; global sessions; deep dynamic; click rate ... See more keywords
Position-Aware Deep Character-Level CTR Prediction for Sponsored Search
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2019.2941881
Abstract: Predicting the click-through rate of an advertisement is a critical component of online advertising platforms. In sponsored search, the click-through rate estimates the probability that a displayed advertisement is clicked by a user after she… read more here.
Keywords: click rate; sponsored search; level; character level ... See more keywords
Feature-Interaction-Enhanced Sequential Transformer for Click-Through Rate Prediction
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DOI: 10.3390/app14072760
Abstract: Click-through rate (CTR) prediction plays a crucial role in online services and applications, such as online shopping and advertising. The performance of CTR prediction can have a direct impact on user experience and the revenue… read more here.
Keywords: click rate; prediction; attention; feature interaction ... See more keywords
Click-through Rate Prediction and Uncertainty Quantification Based on Bayesian Deep Learning
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DOI: 10.3390/e25030406
Abstract: Click-through rate (CTR) prediction is a research point for measuring recommendation systems and calculating AD traffic. Existing studies have proved that deep learning performs very well in prediction tasks, but most of the existing studies… read more here.
Keywords: uncertainty; click rate; prediction; deep learning ... See more keywords
Se-xDeepFEFM: Combining Low-Order Feature Refinement and Interaction Intensity Evaluation for Click-Through Rate Prediction
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DOI: 10.3390/sym14102123
Abstract: Click-through rate (CTR) prediction can provide considerable economic and social benefits. Few studies have considered the importance of low-order features, usually employing a simple feature interaction method. To address these issues, we propose a novel… read more here.
Keywords: interaction; feature; click rate; prediction ... See more keywords
GATI-RS model using Bi-LSTM and multi-head attention mechanism to enhance online shopping experience for the elderly with accurate click-through rate prediction
Sign Up to like & getrecommendations! Published in 2025 at "PeerJ Computer Science"
DOI: 10.7717/peerj-cs.2707
Abstract: With the rapid development of e-commerce and the increasing aging population, more elderly people are engaging in online shopping. However, challenges they face during this process are becoming more apparent. This article proposes a recommendation… read more here.
Keywords: click rate; enhance online; online shopping; prediction ... See more keywords