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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/vumaasha/atlas

공식 코드

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

https://github.com/wbsg-uni-mannheim/pie_chatgpt

공식 코드

Product Information Extraction using ChatGPT

https://github.com/wbsg-uni-mannheim/wdc-pave

공식 코드

Using LLMs for the Extraction and Normalization of Product Attribute Values

https://github.com/xguo7/automatic-controllable-product-copywriting-for-e-commerce

공식 코드

Automatic Controllable Product Copywriting for E-Commerce

https://github.com/xinyiyan/duelingbandits

공식 코드

Human Preferences as Dueling Bandits

https://github.com/xmc-aalto/inceptionxml

공식 코드

InceptionXML: A Lightweight Framework with Synchronized Negative Sampling for Short Text Extreme Classification

https://github.com/yourh/AttentionXML

공식 코드

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

https://github.com/yusanshi/LSEC-GNN

공식 코드

Leveraging Tripartite Interaction Information from Live Stream E-Commerce for Improving Product Recommendation

https://github.com/zhen-tan-dmml/tlp-fsnc

공식 코드

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

https://github.com/AemikaChow/DATASOURCE

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

https://github.com/BBloggsbott/k-armed-bandits

A Tutorial on Thompson Sampling

https://github.com/Ducvoccer/mildnet

Retrieving Similar E-Commerce Images Using Deep Learning

https://github.com/JerryKwon/melon_plylst_continuation

Taming Pretrained Transformers for Extreme Multi-label Text Classification

https://github.com/JieyuZ2/TMN

TaxoExpan: Self-supervised Taxonomy Expansion with Position-Enhanced Graph Neural Network

https://github.com/NeuromorphicComputationResearchProgram/Learning-with-Holographic-Reduced-Representations

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

https://github.com/SY1706203/GATNE

Representation Learning for Attributed Multiplex Heterogeneous Network

https://github.com/THUDM/GATNE

Representation Learning for Attributed Multiplex Heterogeneous Network

https://github.com/appier/compatibility-family-learning

Learning Compatibility Across Categories for Heterogeneous Item Recommendation

https://github.com/ciol-researchlab/SupplyGraph

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

https://github.com/ciol-sust/supplygraph

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

https://github.com/dmlc/dgl/tree/master/examples/pytorch/GATNE-T

Representation Learning for Attributed Multiplex Heterogeneous Network

https://github.com/hamedrab/forec

Cross-Market Product Recommendation

https://github.com/khatria/Retrieving-Similar-E-Commerce-Images-Using-Deep-Learning

Retrieving Similar E-Commerce Images Using Deep Learning

https://github.com/mankmonjre/k-DPP-reco-engine

Low-Rank Factorization of Determinantal Point Processes for Recommendation

https://github.com/mickeysjm/taxoexpan

TaxoExpan: Self-supervised Taxonomy Expansion with Position-Enhanced Graph Neural Network

https://github.com/splintr-ml/splintr/blob/master/splintr/dataparallel/isubnet.py

Distributed Learning of Deep Neural Networks using Independent Subnet Training

https://github.com/xmc-aalto/adv-xmtc

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

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.