Projects per year
Personal profile
Research Interests
Data Mining、Recommender Systems、Intelligent Data Analysis
Education/Academic qualification
PhD, Computer Science, University of Minnesota Twin Cities
External positions
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Research on Deep Learning Models for Tag Recommendation based on Topics, Popular Search Terms and Group Articles
1/08/22 → 31/07/23
Project: Government Ministry › Other Government Ministry Institute
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Research on Deep Learning Models for Tag Recommendation based on Topics, Popular Search Terms and Group Articles
1/08/21 → 31/07/22
Project: Government Ministry › Other Government Ministry Institute
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Research on Deep Learning and Generative Adversarial Network Models for Document Recommendation
1/08/20 → 31/07/21
Project: Government Ministry › Other Government Ministry Institute
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Research on Deep Learning and Generative Adversarial Network Models for Document Recommendation
1/08/19 → 31/07/20
Project: Government Ministry › Other Government Ministry Institute
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Research on Online Recommendation Methods with Cross-Domain Interest Analysis for Integrated Online News and e-Commerce Web Platforms
1/08/18 → 31/07/19
Project: Government Ministry › Other Government Ministry Institute
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A boosting resampling method for regression based on a conditional variational autoencoder
Huang, Y., Liu, D. R., Lee, S. J., Hsu, C. H. & Liu, Y. G., Apr 2022, In: Information sciences. 590, p. 90-105 16 p.Research output: Contribution to journal › Article › peer-review
2 Scopus citations -
Credit default swap prediction based on generative adversarial networks
Lin, S. Y., Liu, D. R. & Huang, H. P., 2022, (Accepted/In press) In: Data Technologies and Applications.Research output: Contribution to journal › Article › peer-review
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Online Product Recommendations based on Diversity and Latent Association Analysis on News and Products
Chen, H. Y., Lin, Y. C., Liu, D. R. & Liu, T. F., Sep 2022, In: Journal of Information Science and Engineering. 38, 5, p. 1065-1085 21 p.Research output: Contribution to journal › Article › peer-review
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Random RotBoost: An Ensemble Classification Method Based on Rotation Forest and AdaBoost in Random Subsets and Its Application to Clinical Decision Support
Lee, S. J., Tseng, C. H., Yang, H. Y., Jin, X., Jiang, Q., Pu, B., Hu, W. H., Liu, D. R., Huang, Y. & Zhao, N., May 2022, In: Entropy. 24, 5, 617.Research output: Contribution to journal › Article › peer-review
Open Access4 Scopus citations -
A hybrid of XGBoost and aspect-based review mining with attention neural network for user preference prediction
Lai, C. H., Liu, D-R. & Lien, K. S., May 2021, In: International Journal of Machine Learning and Cybernetics. 12, 5, p. 1203–1217Research output: Contribution to journal › Article › peer-review
6 Scopus citations