Click-Through Rate Prediction Models based on Interest Modeling

doi:10.1145/3640872.3640876

科研成果详情

题名	Click-Through Rate Prediction Models based on Interest Modeling
作者	Luo，Zhen 1; Zhang，Yingfang 2; Hu，Chengxuan 3; Xia，Yuxuan 4; Zhu，Shengxin5
发表日期	2023-11-17
会议录名称	ACM International Conference Proceeding Series
页码	18-27
摘要	Deep learning frameworks have achieved extraordinary results in popular technological frontiers, which also greatly inspires considerable researchers in recommender system. As one of the mainstream research frontiers, click-through rate (CTR) predictions have received increasing attention from both industrial and academic circles. Recently, Alibaba group has come up with novel idea of interest modeling that can effectively overcome the limitations brought by previous deep learning CTR prediction models, which is also the key to improve performance. For the past few years, more and more relevant works begin to explore approaches taking advantage of the learning, representation, and interpretation ability from neural networks. However, there are few comprehensive surveys targeted at this topic. In this paper, we systematically review and summarize recent CTR prediction models based on interest modeling. First, we elaborate their different design ideas and pay additional attention to their intrinsic relationship including improvements and extensions, similarities and differences, advantages and disadvantages and so on. Next, we deploy them separately according to official open-source code and compare their performance assessment in terms of accuracy and speed, looking for best optimizers and other hyperparameters. Furthermore, we briefly discuss some possible refinement directions and future research trends.
关键词	behavior modeling click-through rate prediction deep learning neural recommendation model recommender system
DOI	10.1145/3640872.3640876
URL	查看来源
语种	英语English
Scopus入藏号	2-s2.0-85186507075
引用统计
文献类型	会议论文
条目标识符	https://repository.uic.edu.cn/handle/39GCC9TT/11498
专题	北师香港浸会大学
通讯作者	Luo，Zhen
作者单位	1.Department of Statistical Science,University College London,United Kingdom 2.Department of Statistics and Actuarial Science,University of Hong Kong,Hong Kong,Hong Kong 3.Department of Industrial and Systems Engineering,Polytechnic University of Hong Kong,Hong Kong,Hong Kong 4.School of Mathematics,University of Southampton,United Kingdom 5.Research Center for Mathematics,Advanced Institute of Natural Science,Beijing Normal University,Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science,BNU-HKBU United International College,China
推荐引用方式 GB/T 7714	Luo，Zhen,Zhang，Yingfang,Hu，Chengxuanet al. Click-Through Rate Prediction Models based on Interest Modeling[C], 2023: 18-27.