Search Results for author: Quan Lin

Found 5 papers, 1 papers with code

Reinforcement Re-ranking with 2D Grid-based Recommendation Panels

no code implementations11 Apr 2022 Sirui Chen, Xiao Zhang, Xu Chen, Zhiyu Li, YuAn Wang, Quan Lin, Jun Xu

Presenting items in grid-based result panels poses new challenges to recommender systems because existing models are all designed to output sequential lists while the slots in a grid-based panel have no explicit order.

Recommendation Systems Re-Ranking

Entire Space Multi-Task Modeling via Post-Click Behavior Decomposition for Conversion Rate Prediction

no code implementations15 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.

Click-Through Rate Prediction Multi-Task Learning +2

SDM: Sequential Deep Matching Model for Online Large-scale Recommender System

2 code implementations1 Sep 2019 Fuyu Lv, Taiwei Jin, Changlong Yu, Fei Sun, Quan Lin, Keping Yang, Wilfred Ng

In this paper, we propose a new sequential deep matching (SDM) model to capture users' dynamic preferences by combining short-term sessions and long-term behaviors.

Collaborative Filtering Recommendation Systems

Multi-Level Deep Cascade Trees for Conversion Rate Prediction in Recommendation System

no code implementations24 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.

Click-Through Rate Prediction Ensemble Learning

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