update

Author: tangxyw

Industry/Disentangling Long and Short-Term Interests for Recommendation.pdf

@@ -2,7 +2,7 @@
 # 推荐系统相关论文汇总
 ([English Version is Here](/README_EN.md))
 ## 介绍
-1. 截至2023-03-24，本仓库收集汇总了推荐系统领域相关论文共**640**篇，涉及：**召回**，**粗排**，**精排**，**重排**，**多任务**，**多场景**，**多模态**，**冷启动**，**校准**，
+1. 截至2023-03-27，本仓库收集汇总了推荐系统领域相关论文共**642**篇，涉及：**召回**，**粗排**，**精排**，**重排**，**多任务**，**多场景**，**多模态**，**冷启动**，**校准**，
 **纠偏**，**多样性**，**公平性**，**反馈延迟**，**蒸馏**，**对比学习**，**因果推断**，**Look-Alike**，**Learning-to-Rank**，**强化学习**等领域，本仓库会跟踪业界进展，持续更新。
 2. 因文件名特殊字符的限制，故论文title中所有的`:`都改为了`-`，检索时请注意。
 3. 文件名前缀中带有`[]`的，表明本人已经通读过，第一个`[]`中为论文年份，第二个`[]`中为发表机构或公司(可选)，第三个`[]`中为论文提出的model或method的简称(可选)。
@@ -99,6 +99,7 @@
 - [Deep Spatio-Temporal Neural Networks for Click-Through Rate Prediction](Industry/Deep%20Spatio-Temporal%20Neural%20Networks%20for%20Click-Through%20Rate%20Prediction.pdf)
 - [Denoising Neural Network for News Recommendation with Positive and Negative Implicit Feedback](Industry/Denoising%20Neural%20Network%20for%20News%20Recommendation%20with%20Positive%20and%20Negative%20Implicit%20Feedback.pdf)
 - [Denoising User-aware Memory Network for Recommendation](Industry/Denoising%20User-aware%20Memory%20Network%20for%20Recommendation.pdf)
+- [Disentangling Long and Short-Term Interests for Recommendation](Industry/Disentangling%20Long%20and%20Short-Term%20Interests%20for%20Recommendation.pdf)
 - [E-Commerce Item Recommendation Based on Field-aware Factorization Machine](Industry/E-Commerce%20Item%20Recommendation%20Based%20on%20Field-aware%20Factorization%20Machine.pdf)
 - [EXTR - Click-Through Rate Prediction with Externalities in E-Commerce Sponsored Search](Industry/EXTR%20-%20Click-Through%20Rate%20Prediction%20with%20Externalities%20in%20E-Commerce%20Sponsored%20Search.pdf)
 - [End-to-End User Behavior Retrieval in Click-Through Rate Prediction Model](Industry/End-to-End%20User%20Behavior%20Retrieval%20in%20Click-Through%20Rate%20Prediction%20Model.pdf)
@@ -108,6 +109,7 @@
 - [FLEN - Leveraging Field for Scalable CTR Prediction](Industry/FLEN%20-%20Leveraging%20Field%20for%20Scalable%20CTR%20Prediction.pdf)
 - [FiBiNet++ - Improving FiBiNet by Greatly Reducing Model Size for CTR Prediction](Industry/FiBiNet%2B%2B%20-%20Improving%20FiBiNet%20by%20Greatly%20Reducing%20Model%20Size%20for%20CTR%20Prediction.pdf)
 - [GateNet - Gating-Enhanced Deep Network for Click-Through Rate Prediction](Industry/GateNet%20-%20Gating-Enhanced%20Deep%20Network%20for%20Click-Through%20Rate%20Prediction.pdf)
+- [Hierarchically Fusing Long and Short-Term User Interests for Click-Through Rate Prediction in Product Search](Industry/Hierarchically%20Fusing%20Long%20and%20Short-Term%20User%20Interests%20for%20Click-Through%20Rate%20Prediction%20in%20Product%20Search.pdf)
 - [Hybrid Interest Modeling for Long-tailed Users](Industry/Hybrid%20Interest%20Modeling%20for%20Long-tailed%20Users.pdf)
 - [Hierarchical Gating Networks for Sequential Recommendation](Industry/Hierarchical%20Gating%20Networks%20for%20Sequential%20Recommendation.pdf)
 - [HIEN - Hierarchical Intention Embedding Network for Click-Through Rate Prediction](Industry/HIEN%20-%20Hierarchical%20Intention%20Embedding%20Network%20for%20Click-Through%20Rate%20Prediction.pdf)

Industry/Hierarchically Fusing Long and Short-Term User Interests for Click-Through Rate Prediction in Product Search.pdf

@@ -1,7 +1,7 @@
 
 # Summary of Papers Related to Recommendation System
 ## Introduce
-1. Up to 2023-03-24, **640** papers related to recommendation system have been collected and summarized in this repo, 
+1. Up to 2023-03-27, **642** papers related to recommendation system have been collected and summarized in this repo, 
 including: **Match**, **Pre-Rank**, **Rank**, **Re-Rank**, **Multi-Task**, **Multi-Scenario**, **Multi-Modal**, **Cold-Start**, **Calibration**, 
 **Debias**, **Diversity**, **Fairness**, **Feedback-Delay**, **Distillation**, **Contrastive Learning**, **Casual Inference**, 
 **Look-Alike**, **Learning-to-Rank**, **Reinforcement Learning** and other fields, the repo will track the industry progress and update continuely.
@@ -106,6 +106,7 @@ I will remove it immediately after verification.
 - [Deep Spatio-Temporal Neural Networks for Click-Through Rate Prediction](Industry/Deep%20Spatio-Temporal%20Neural%20Networks%20for%20Click-Through%20Rate%20Prediction.pdf)
 - [Denoising Neural Network for News Recommendation with Positive and Negative Implicit Feedback](Industry/Denoising%20Neural%20Network%20for%20News%20Recommendation%20with%20Positive%20and%20Negative%20Implicit%20Feedback.pdf)
 - [Denoising User-aware Memory Network for Recommendation](Industry/Denoising%20User-aware%20Memory%20Network%20for%20Recommendation.pdf)
+- [Disentangling Long and Short-Term Interests for Recommendation](Industry/Disentangling%20Long%20and%20Short-Term%20Interests%20for%20Recommendation.pdf)
 - [E-Commerce Item Recommendation Based on Field-aware Factorization Machine](Industry/E-Commerce%20Item%20Recommendation%20Based%20on%20Field-aware%20Factorization%20Machine.pdf)
 - [EXTR - Click-Through Rate Prediction with Externalities in E-Commerce Sponsored Search](Industry/EXTR%20-%20Click-Through%20Rate%20Prediction%20with%20Externalities%20in%20E-Commerce%20Sponsored%20Search.pdf)
 - [End-to-End User Behavior Retrieval in Click-Through Rate Prediction Model](Industry/End-to-End%20User%20Behavior%20Retrieval%20in%20Click-Through%20Rate%20Prediction%20Model.pdf)
@@ -115,6 +116,7 @@ I will remove it immediately after verification.
 - [FLEN - Leveraging Field for Scalable CTR Prediction](Industry/FLEN%20-%20Leveraging%20Field%20for%20Scalable%20CTR%20Prediction.pdf)
 - [FiBiNet++ - Improving FiBiNet by Greatly Reducing Model Size for CTR Prediction](Industry/FiBiNet%2B%2B%20-%20Improving%20FiBiNet%20by%20Greatly%20Reducing%20Model%20Size%20for%20CTR%20Prediction.pdf)
 - [GateNet - Gating-Enhanced Deep Network for Click-Through Rate Prediction](Industry/GateNet%20-%20Gating-Enhanced%20Deep%20Network%20for%20Click-Through%20Rate%20Prediction.pdf)
+- [Hierarchically Fusing Long and Short-Term User Interests for Click-Through Rate Prediction in Product Search](Industry/Hierarchically%20Fusing%20Long%20and%20Short-Term%20User%20Interests%20for%20Click-Through%20Rate%20Prediction%20in%20Product%20Search.pdf)
 - [Hybrid Interest Modeling for Long-tailed Users](Industry/Hybrid%20Interest%20Modeling%20for%20Long-tailed%20Users.pdf)
 - [Hierarchical Gating Networks for Sequential Recommendation](Industry/Hierarchical%20Gating%20Networks%20for%20Sequential%20Recommendation.pdf)
 - [HIEN - Hierarchical Intention Embedding Network for Click-Through Rate Prediction](Industry/HIEN%20-%20Hierarchical%20Intention%20Embedding%20Network%20for%20Click-Through%20Rate%20Prediction.pdf)