Bangzuo Zhang

Orcid: 0000-0002-3438-6795

According to our database1, Bangzuo Zhang authored at least 18 papers between 2008 and 2023.

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Bibliography

2023
Relationship-aware contrastive learning for social recommendations.
Inf. Sci., June, 2023

2021
Attribute-aware deep attentive recommendation.
J. Supercomput., 2021

KCRec: Knowledge-aware representation Graph Convolutional Network for Recommendation.
Knowl. Based Syst., 2021

2020
Adaptive Deep Modeling of Users and Items Using Side Information for Recommendation.
IEEE Trans. Neural Networks Learn. Syst., 2020

Deep Plot-Aware Generalized Matrix Factorization for Collaborative Filtering.
Neural Process. Lett., 2020

Extreme Residual Connected Convolution-Based Collaborative Filtering for Document Context-Aware Rating Prediction.
IEEE Access, 2020

2019
Trust-Aware Collaborative Filtering with a Denoising Autoencoder.
Neural Process. Lett., 2019

Integrating an Attention Mechanism and Convolution Collaborative Filtering for Document Context-Aware Rating Prediction.
IEEE Access, 2019

2018
A probabilistic model derived term weighting scheme for text classification.
Pattern Recognit. Lett., 2018

Multiple Auxiliary Information Based Deep Model for Collaborative Filtering.
J. Comput. Sci. Technol., 2018

2017
一种基于Bhattacharyya系数和项目相关性的协同过滤算法 (Collaborative Filtering Algorithm Based on Bhattacharyya Coefficient and Item Correlation).
计算机科学, 2017

2016
A New Weighted Similarity Method Based on Neighborhood User Contributions for Collaborative Filtering.
Proceedings of the IEEE First International Conference on Data Science in Cyberspace, 2016

A Novel Recommendation Method Based on User's Interest and Heterogeneous Information.
Proceedings of the Web Technologies and Applications, 2016

2015
A Novel Recommendation Algorithm Based on Heterogeneous Information Network Similarity and Preference Diffusion.
Proceedings of the Web-Age Information Management, 2015

2009
Reliable Negative Extracting Based on kNN for Learning from Positive and Unlabeled Examples.
J. Comput., 2009

2008
Learning from Positive and Unlabeled Examples: A Survey.
Proceedings of the International Symposium on Information Processing, 2008

Tri-Training Based Learning from Positive and Unlabeled Data.
Proceedings of the International Symposium on Information Processing, 2008

A Novel Reliable Negative Method Based on Clustering for Learning from Positive and Unlabeled Examples.
Proceedings of the Information Retrieval Technology, 2008


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