Search Results for author: Stephen Guo

Found 15 papers, 4 papers with code

Click-Conversion Multi-Task Model with Position Bias Mitigation for Sponsored Search in eCommerce

no code implementations29 Jul 2023 Yibo Wang, Yanbing Xue, Bo Liu, Musen Wen, Wenting Zhao, Stephen Guo, Philip S. Yu

Position bias, the phenomenon whereby users tend to focus on higher-ranked items of the search result list regardless of the actual relevance to queries, is prevailing in many ranking systems.

Position

Mitigating Frequency Bias in Next-Basket Recommendation via Deconfounders

no code implementations16 Nov 2022 Xiaohan Li, Zheng Liu, Luyi Ma, Kaushiki Nag, Stephen Guo, Philip Yu, Kannan Achan

Considering the influence of historical purchases on users' future interests, the user and item representations can be viewed as unobserved confounders in the causal diagram.

Causal Inference Fairness +2

Causal Structure Learning with Recommendation System

no code implementations19 Oct 2022 Shuyuan Xu, Da Xu, Evren Korpeoglu, Sushant Kumar, Stephen Guo, Kannan Achan, Yongfeng Zhang

Discovering the causal mechanism from RS feedback data is both novel and challenging, since RS itself is a source of intervention that can influence both the users' exposure and their willingness to interact.

Decision Making Recommendation Systems

Generating Rich Product Descriptions for Conversational E-commerce Systems

no code implementations30 Nov 2021 Shashank Kedia, Aditya Mantha, Sneha Gupta, Stephen Guo, Kannan Achan

We propose eBERT, a sequence-to-sequence approach by further pre-training the BERT embeddings on an e-commerce product description corpus, and then fine-tuning the resulting model to generate short, natural, spoken language titles from input web titles.

Sentence

Pre-training Recommender Systems via Reinforced Attentive Multi-relational Graph Neural Network

no code implementations28 Nov 2021 Xiaohan Li, Zhiwei Liu, Stephen Guo, Zheng Liu, Hao Peng, Philip S. Yu, Kannan Achan

In this paper, we propose a novel Reinforced Attentive Multi-relational Graph Neural Network (RAM-GNN) to the pre-train user and item embeddings on the user and item graph prior to the recommendation step.

Recommendation Systems

PairRank: Online Pairwise Learning to Rank by Divide-and-Conquer

1 code implementation28 Feb 2021 Yiling Jia, Huazheng Wang, Stephen Guo, Hongning Wang

Online Learning to Rank (OL2R) eliminates the need of explicit relevance annotation by directly optimizing the rankers from their interactions with users.

Learning-To-Rank

A Real-Time Whole Page Personalization Framework for E-Commerce

no code implementations8 Dec 2020 Aditya Mantha, Anirudha Sundaresan, Shashank Kedia, Yokila Arora, Shubham Gupta, Gaoyang Wang, Praveenkumar Kanumala, Stephen Guo, Kannan Achan

In production, our system resulted in an improvement in item discovery, an increase in online engagement, and a significant lift on add-to-carts (ATCs) per visitor on the homepage.

An End-to-End ML System for Personalized Conversational Voice Models in Walmart E-Commerce

no code implementations2 Nov 2020 Rahul Radhakrishnan Iyer, Praveenkumar Kanumala, Stephen Guo, Kannan Achan

Searching for and making decisions about products is becoming increasingly easier in the e-commerce space, thanks to the evolution of recommender systems.

Recommendation Systems

Basket Recommendation with Multi-Intent Translation Graph Neural Network

1 code implementation22 Oct 2020 Zhiwei Liu, Xiaohan Li, Ziwei Fan, Stephen Guo, Kannan Achan, Philip S. Yu

The problem of basket recommendation~(BR) is to recommend a ranking list of items to the current basket.

Relation Translation

Product Title Generation for Conversational Systems using BERT

no code implementations23 Jul 2020 Mansi Ranjit Mane, Shashank Kedia, Aditya Mantha, Stephen Guo, Kannan Achan

Through recent advancements in speech technology and introduction of smart devices, such as Amazon Alexa and Google Home, increasing number of users are interacting with applications through voice.

BasConv: Aggregating Heterogeneous Interactions for Basket Recommendation with Graph Convolutional Neural Network

1 code implementation14 Jan 2020 Zhiwei Liu, Mengting Wan, Stephen Guo, Kannan Achan, Philip S. Yu

By defining a basket entity to represent the basket intent, we can model this problem as a basket-item link prediction task in the User-Basket-Item~(UBI) graph.

Collaborative Filtering Link Prediction

A Large-Scale Deep Architecture for Personalized Grocery Basket Recommendations

no code implementations24 Oct 2019 Aditya Mantha, Yokila Arora, Shubham Gupta, Praveenkumar Kanumala, Zhiwei Liu, Stephen Guo, Kannan Achan

In this paper, we introduce a production within-basket grocery recommendation system, RTT2Vec, which generates real-time personalized product recommendations to supplement the user's current grocery basket.

Complementary-Similarity Learning using Quadruplet Network

1 code implementation26 Aug 2019 Mansi Ranjit Mane, Stephen Guo, Kannan Achan

We propose a novel learning framework to answer questions such as "if a user is purchasing a shirt, what other items will (s)he need with the shirt?"

Small Boxes Big Data: A Deep Learning Approach to Optimize Variable Sized Bin Packing

no code implementations14 Feb 2017 Feng Mao, Edgar Blanco, Mingang Fu, Rohit Jain, Anurag Gupta, Sebastien Mancel, Rong Yuan, Stephen Guo, Sai Kumar, Yayang Tian

We introduce a deep learning approach to overcome the drawbacks by applying a large training data set, auto feature selection and fast, accurate labeling.

Feature Engineering feature selection

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