TransNFCM: translation-based neural fashion compatibility modeling

TransNFCM: translation-based neural fashion compatibility modeling

Identifying mix-and-match relationships between fashion items is an urgent task in a fashion e-commerce recommender system. It will significantly enhance user experience and satisfaction. However, due to the challenges of inferring the rich yet complicated set of compatibility patterns in a large e-...

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Bibliographic Details
Main Authors: YANG, Xun, MA, Yunshan, LIAO, Lizi, WANG, Meng, CHUA, Tat-Seng
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2019
Subjects:
Arts computing
Deep learning
Deep neural networks
Embeddings
Knowledge representation
Product design
User experience
Vector spaces
Artificial Intelligence and Robotics
Online Access:https://ink.library.smu.edu.sg/sis_research/7570
https://ink.library.smu.edu.sg/context/sis_research/article/8573/viewcontent/TransNFCM_translation_based_neural_fashion_compatibility_modeling.pdf
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Institution: Singapore Management University
Language: English

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https://ink.library.smu.edu.sg/sis_research/7570
https://ink.library.smu.edu.sg/context/sis_research/article/8573/viewcontent/TransNFCM_translation_based_neural_fashion_compatibility_modeling.pdf

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