Product Recommendation
34 papers with code • 1 benchmarks • 8 datasets
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Latest papers
Using LLMs for the Extraction and Normalization of Product Attribute Values
For our experiments, we introduce the WDC Product Attribute-Value Extraction (WDC PAVE) dataset.
RetailSynth: Synthetic Data Generation for Retail AI Systems Evaluation
Significant research effort has been devoted in recent years to developing personalized pricing, promotions, and product recommendation algorithms that can leverage rich customer data to learn and earn.
Multi-modal Extreme Classification
This paper develops the MUFIN technique for extreme classification (XC) tasks with millions of labels where datapoints and labels are endowed with visual and textual descriptors.
Scaling Session-Based Transformer Recommendations using Optimized Negative Sampling and Loss Functions
This work introduces TRON, a scalable session-based Transformer Recommender using Optimized Negative-sampling.
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation
To test the potential of the dataset, we introduce three tasks in this work: (1) next-product recommendation, (2) next-product recommendation with domain shifts, and (3) next-product title generation.
Product Information Extraction using ChatGPT
Hence, extracting attribute/value pairs from textual product descriptions is an essential enabler for e-commerce applications.
Optimal Low-Rank Matrix Completion: Semidefinite Relaxations and Eigenvector Disjunctions
Low-rank matrix completion consists of computing a matrix of minimal complexity that recovers a given set of observations as accurately as possible.
Let Graph be the Go Board: Gradient-free Node Injection Attack for Graph Neural Networks via Reinforcement Learning
Whereas for the node injection attack, though being more practical, current approaches require training surrogate models to simulate a white-box setting, which results in significant performance downgrade when the surrogate architecture diverges from the actual victim model.
Automatic Controllable Product Copywriting for E-Commerce
Automatic product description generation for e-commerce has witnessed significant advancement in the past decade.
Learning Backward Compatible Embeddings
We formalize the problem where the goal is for the embedding team to keep updating the embedding version, while the consumer teams do not have to retrain their models.