no code implementations • 12 Nov 2023 • Zhenghao Liu, Zulong Chen, Moufeng Zhang, Shaoyang Duan, Hong Wen, Liangyue Li, Nan Li, Yu Gu, Ge Yu
This paper proposes the User Viewing Flow Modeling (SINGLE) method for the article recommendation task, which models the user constant preference and instant interest from user-clicked articles.
no code implementations • 16 Apr 2023 • Peilin Chen, Hong Wen, Jing Zhang, Fuyu Lv, Zhao Li, Qijie Shen, Wanjie Tao, Ying Zhou, Chao Zhang
Online travel platforms (OTPs), e. g., Ctrip. com or Fliggy. com, can effectively provide travel-related products or services to users.
no code implementations • 4 Apr 2023 • Qijie Shen, Hong Wen, Jing Zhang, Qi Rao
Specifically, SIE is proposed to extract user's short-term interests by integrating three fundamental interests encoders within it namely query-dependent, target-dependent and causal-dependent interest encoder, respectively, followed by delivering the resultant representation to the module LIE, where it can effectively capture user long-term interests by devising an attention mechanism with respect to the short-term interests from SIE module.
no code implementations • 6 Jul 2022 • Jiazhen Lou, Hong Wen, Fuyu Lv, Jing Zhang, Tengfei Yuan, Zhao Li
Recommender Systems (RS), as an efficient tool to discover users' interested items from a very large corpus, has attracted more and more attention from academia and industry.
1 code implementation • 5 Feb 2022 • Qijie Shen, Hong Wen, Wanjie Tao, Jing Zhang, Fuyu Lv, Zulong Chen, Zhao Li
In many classical e-commerce platforms, personalized recommendation has been proven to be of great business value, which can improve user satisfaction and increase the revenue of platforms.
no code implementations • 27 Dec 2021 • Xiaofeng Pan, Ming Li, Jing Zhang, Keren Yu, Luping Wang, Hong Wen, Chengjun Mao, Bo Cao
At last, we develop an Ensemble Prediction Network (EPN) which incorporates the output of FRN and DMN to make the final CVR prediction.
1 code implementation • 27 Dec 2021 • Xiaofeng Pan, Yibin Shen, Jing Zhang, Xu He, Yang Huang, Hong Wen, Chengjun Mao, Bo Cao
In this paper, we propose a novel CTR model named MOEF for recommendations under frequent changes of occasions.
no code implementations • 13 Oct 2021 • Qijie Shen, Wanjie Tao, Jing Zhang, Hong Wen, Zulong Chen, Quan Lu
In this paper, we propose a novel Scenario-Aware Ranking Network (SAR-Net) to address these issues.
no code implementations • 20 Apr 2021 • Hong Wen, Jing Zhang, Fuyu Lv, Wentian Bao, Tianyi Wang, Zulong Chen
Motivated by this observation, we propose a novel \emph{CVR} prediction method by Hierarchically Modeling both Micro and Macro behaviors ($HM^3$).
no code implementations • 16 Oct 2019 • Wenhao Zhang, Wentian Bao, Xiao-Yang Liu, Keping Yang, Quan Lin, Hong Wen, Ramin Ramezani
In addition, our methods are based on the multi-task learning framework and mitigate the data sparsity issue.
no code implementations • 15 Oct 2019 • Hong Wen, Jing Zhang, Yu-An Wang, Fuyu Lv, Wentian Bao, Quan Lin, Keping Yang
Although existing methods, typically built on the user sequential behavior path ``impression$\to$click$\to$purchase'', is effective for dealing with SSB issue, they still struggle to address the DS issue due to rare purchase training samples.
no code implementations • 24 May 2018 • Hong Wen, Jing Zhang, Quan Lin, Keping Yang, Pipei Huang
The deep cascade structure and the combination rule enable the proposed \textit{ldcTree} to have a stronger distributed feature representation ability.