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05/17/2023
Knowledge Graph Completion Models are Few-shot Learners: An Empirical Study of Relation Labeling in E-commerce with LLMs
Knowledge Graphs (KGs) play a crucial role in enhancing e-commerce syste...
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11/16/2022
Mitigating Frequency Bias in Next-Basket Recommendation via Deconfounders
Recent studies on Next-basket Recommendation (NBR) have achieved much pr...
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02/11/2022
NEAT: A Label Noise-resistant Complementary Item Recommender System with Trustworthy Evaluation
The complementary item recommender system (CIRS) recommends the compleme...
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11/30/2021
Generating Rich Product Descriptions for Conversational E-commerce Systems
Through recent advancements in speech technologies and introduction of s...
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11/28/2021
Pre-training Recommender Systems via Reinforced Attentive Multi-relational Graph Neural Network
Recently, Graph Neural Networks (GNNs) have proven their effectiveness f...
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10/23/2021
Rethinking Neural vs. Matrix-Factorization Collaborative Filtering: the Theoretical Perspectives
The recent work by Rendle et al. (2020), based on empirical observations...
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10/23/2021
Towards the D-Optimal Online Experiment Design for Recommender Selection
Selecting the optimal recommender via online exploration-exploitation is...
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04/15/2021
Variational Inference for Category Recommendation in E-Commerce platforms
Category recommendation for users on an e-Commerce platform is an import...
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03/28/2021
A Temporal Kernel Approach for Deep Learning with Continuous-time Information
Sequential deep learning models such as RNN, causal CNN and attention me...
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02/24/2021
Theoretical Understandings of Product Embedding for E-commerce Machine Learning
Product embeddings have been heavily investigated in the past few years,...
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12/12/2020
GAN-based Recommendation with Positive-Unlabeled Sampling
Recommender systems are popular tools for information retrieval tasks on...
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12/08/2020
A Real-Time Whole Page Personalization Framework for E-Commerce
E-commerce platforms consistently aim to provide personalized recommenda...
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12/04/2020
On Detecting Data Pollution Attacks On Recommender Systems Using Sequential GANs
Recommender systems are an essential part of any e-commerce platform. Re...
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12/02/2020
On Variational Inference for User Modeling in Attribute-Driven Collaborative Filtering
Recommender Systems have become an integral part of online e-Commerce pl...
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11/08/2020
Adversarial Counterfactual Learning and Evaluation for Recommender System
The feedback data of recommender systems are often subject to what was e...
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11/02/2020
An End-to-End ML System for Personalized Conversational Voice Models in Walmart E-Commerce
Searching for and making decisions about products is becoming increasing...
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10/22/2020
Basket Recommendation with Multi-Intent Translation Graph Neural Network
The problem of basket recommendation (BR) is to recommend a ranking list...
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07/23/2020
Product Title Generation for Conversational Systems using BERT
Through recent advancements in speech technology and introduction of sma...
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02/19/2020
Inductive Representation Learning on Temporal Graphs
Inductive representation learning on temporal graphs is an important ste...
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01/14/2020
BasConv: Aggregating Heterogeneous Interactions for Basket Recommendation with Graph Convolutional Neural Network
Within-basket recommendation reduces the exploration time of users, wher...
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11/28/2019
Self-attention with Functional Time Representation Learning
Sequential modelling with self-attention has achieved cutting edge perfo...
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11/28/2019
Product Knowledge Graph Embedding for E-commerce
In this paper, we propose a new product knowledge graph (PKG) embedding ...
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10/24/2019
A Large-Scale Deep Architecture for Personalized Grocery Basket Recommendations
With growing consumer adoption of online grocery shopping through platfo...
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08/26/2019
Complementary-Similarity Learning using Quadruplet Network
We propose a novel learning framework to answer questions such as "if a ...
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03/16/2019
Modeling Complementary Products and Customer Preferences with Context Knowledge for Online Recommendation
Modeling item complementariness and user preferences from purchase data ...
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03/06/2019
Generative Graph Convolutional Network for Growing Graphs
Modeling generative process of growing graphs has wide applications in s...
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08/22/2018
Robust Counterfactual Inferences using Feature Learning and their Applications
In a wide variety of applications, including personalization, we want to...
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01/10/2013