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News recommendations based on collaborative topic modeling and collaborative filtering with generative adversarial networks
Duen Ren Liu
*
, Yang Huang, Jhen Jie Jhao,
Shin Jye Lee
*
此作品的通信作者
資訊管理研究所
科技管理研究所
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Keyphrases
Generative Adversarial Networks
100%
Collaborative Filtering
100%
Preference Learning
100%
Collaborative Topic Modeling
100%
News Recommendation
100%
Parallel Neural Network
57%
Item Contents
57%
News Content
42%
Recommendation Model
42%
News Articles
42%
Network Applications
28%
User Preference
28%
Novel Hybrids
28%
Recommendation Quality
28%
Online News
28%
News Websites
28%
Preference Prediction
28%
Latent Preference
28%
Network-based Recommendation
28%
Design Methodology
14%
Recommendation Method
14%
Latent Topics
14%
Implicit Feedback
14%
Novel Recommendation
14%
Tunable Parameters
14%
User Ratings
14%
News Media
14%
Latent Topic Modeling
14%
Content Information
14%
Media Platforms
14%
Model Modification
14%
Efficient Recommendation
14%
Matrix Factorization
14%
Commercial Value
14%
Content Preferences
14%
Textual Content
14%
Latent Feature
14%
News Users
14%
User Preference Prediction
14%
Preference Feature
14%
News Personalization
14%
History Logs
14%
Computer Science
Generative Adversarial Networks
100%
Collaborative Filtering
100%
Topic Modeling
100%
Preference Learning
87%
Neural Network
50%
User Preference
37%
Content Information
12%
Matrix Factorization
12%
Textual Content
12%