NASM: Nonlinearly Attentive Similarity Model for Recommendation System via Locally Attentive Embedding

NASM: Nonlinearly Attentive Similarity Model for Recommendation System via Locally Attentive Embedding

Recommendation system, as a core service for many customer-oriented online services, is employed to predict the personalized rating of users on their potentially preferable items. In modern industrial settings, an item-based collaborative filtering (item-based CF) method has been long popular owing...

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Bibliographic Details
Main Authors: Zhen-Pei Shan, Yun-Qi Lei, De-Fu Zhang, Jian Zhou
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Locally historical information
globally historical information
nonlinearly attentive layer
locally attentive layer
similarity model
Online Access:https://ieeexplore.ieee.org/document/8715403/

Internet

https://ieeexplore.ieee.org/document/8715403/

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