Collaborative filtering with a deep adversarial and attention network for cross-domain recommendation

Huiting Liu; Lingling Guo; Peipei Li; Peng Zhao; Xindong Wu

doi:10.1016/j.ins.2021.02.009

ScienceGate Book Chapters

JOURNAL ARTICLE

Collaborative filtering with a deep adversarial and attention network for cross-domain recommendation

Huiting Liu Lingling Guo Peipei Li Peng Zhao Xindong Wu

Year: 2021 Journal: Information Sciences Vol: 565 Pages: 370-389 Publisher: Elsevier BV

DOI: 10.1016/j.ins.2021.02.009

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Domain (mathematical analysis) Adversarial system Ranking (information retrieval) Artificial intelligence Collaborative filtering Machine learning Domain knowledge Deep learning Recommender system Data mining Information retrieval Mathematics

Metrics

Cited By

11.65

FWCI (Field Weighted Citation Impact)

Refs

0.98

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Recommender Systems and Techniques

Physical Sciences → Computer Science → Information Systems

Advanced Graph Neural Networks

Physical Sciences → Computer Science → Artificial Intelligence

Domain Adaptation and Few-Shot Learning

Physical Sciences → Computer Science → Artificial Intelligence

Collaborative filtering with a deep adversarial and attention network for cross-domain recommendation

Metrics

Citation History

Topics

Related Documents

Cross-Domain Deep Collaborative Filtering for Recommendation

Collaborative Filtering Recommendation Combining Adversarial Network and Attention Mechanism

LCAN: Light Cross-Attention Network for Collaborative Filtering Recommendation

A Deep Dual Adversarial Network for Cross-Domain Recommendation

Deep Transfer Collaborative Filtering with Geometric Structure Preservation for Cross-Domain Recommendation