Product Recommendation
34 papers with code • 1 benchmarks • 8 datasets
Benchmarks
These leaderboards are used to track progress in Product Recommendation
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Libraries
Use these libraries to find Product Recommendation models and implementationsDatasets
EXTREME CLASSIFICATION
Logo-2K+
VISUELLE2.0
OTTO Recommender Systems Dataset
LSEC
Most implemented papers
Cross-Market Product Recommendation
hamedrab/forec
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We introduce and formalize the problem of cross-market product recommendation, i. e., market adaptation.
InceptionXML: A Lightweight Framework with Synchronized Negative Sampling for Short Text Extreme Classification
Automatic annotation of short-text data to a large number of target labels, referred to as Short Text Extreme Classification, has found numerous applications including prediction of related searches and product recommendation.
Context-aware Retail Product Recommendation with Regularized Gradient Boosting
A total of 167 participants participated in the challenge, and we secured the 6th rank during the final evaluation with an MRR of 0. 4658 on the test set.
Learning Neural Set Functions Under the Optimal Subset Oracle
Learning neural set functions becomes increasingly more important in many applications like product recommendation and compound selection in AI-aided drug discovery.
Balancing Fairness and Accuracy in Sentiment Detection using Multiple Black Box Models
Sentiment detection is an important building block for multiple information retrieval tasks such as product recommendation, cyberbullying detection, and misinformation detection.
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.
Automatic Controllable Product Copywriting for E-Commerce
Automatic product description generation for e-commerce has witnessed significant advancement in the past decade.
Let Graph be the Go Board: Gradient-free Node Injection Attack for Graph Neural Networks via Reinforcement Learning
jumxglhf/g2a2c
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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.
Product Information Extraction using ChatGPT
Hence, extracting attribute/value pairs from textual product descriptions is an essential enabler for e-commerce applications.
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.
