Product Categorization

6 papers with code • 1 benchmarks • 2 datasets

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Datasets


Most implemented papers

AttentionXML: Label Tree-based Attention-Aware Deep Model for High-Performance Extreme Multi-Label Text Classification

yourh/AttentionXML NeurIPS 2019

We propose a new label tree-based deep learning model for XMTC, called AttentionXML, with two unique features: 1) a multi-label attention mechanism with raw text as input, which allows to capture the most relevant part of text to each label; and 2) a shallow and wide probabilistic label tree (PLT), which allows to handle millions of labels, especially for "tail labels".

Graph Neural Networks in Supply Chain Analytics and Optimization: Concepts, Perspectives, Dataset and Benchmarks

CIOL-SUST/SCG 13 Nov 2024

Graph Neural Networks (GNNs) have recently gained traction in transportation, bioinformatics, language and image processing, but research on their application to supply chain management remains limited.

Taming Pretrained Transformers for Extreme Multi-label Text Classification

OctoberChang/X-Transformer 7 May 2019

However, naively applying deep transformer models to the XMC problem leads to sub-optimal performance due to the large output space and the label sparsity issue.

Atlas: A Dataset and Benchmark for E-commerce Clothing Product Categorization

vumaasha/atlas 12 Aug 2019

In E-commerce, it is a common practice to organize the product catalog using product taxonomy.

Transductive Linear Probing: A Novel Framework for Few-Shot Node Classification

zhen-tan-dmml/tlp-fsnc 11 Dec 2022

More recently, inspired by the development of graph self-supervised learning, transferring pretrained node embeddings for few-shot node classification could be a promising alternative to meta-learning but remains unexposed.

SynthesizRR: Generating Diverse Datasets with Retrieval Augmentation

amazon-science/synthesizrr 16 May 2024

It is often desirable to distill the capabilities of large language models (LLMs) into smaller student models due to compute and memory constraints.