Recommender System to Identify Drug-Target Associations Using Matrix Factorization-Reference-Cited by-同舟云学术

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Recommender System to Identify Drug-Target Associations Using Matrix Factorization

Published:2024-01-31 Issue: Volume: Page:539-544
ISSN:
Container-title:2024 Joint International Conference on Digital Arts, Media and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering (ECTI DAMT & NCON)
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Author:

Phuangmalai Sornsawan¹,Suratanee Apichat²,Plaimas Kitiporn³

Affiliation:

1. Chulalongkorn University,Faculty of Science,Department of Mathematics and Computer Science,Bangkok,Thailand

2. King Mongkut’s University of Technology North Bangkok,Faculty of Applied Science, and Intelligent and Nonlinear Dynamic Innovations Research Center,Department of Mathematics,Bangkok,Thailand

3. Faculty of Science, Chulalongkorn University,Advance Virtual and Intelligent Computing (AVIC) Center,Department of Mathematics and Computer Science,Bangkok,Thailand

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10479959/10479962/10480045.pdf?arnumber=10480045

Reference15 articles.

1. A Survey of Collaborative Filtering Techniques

2. Reducing Data Sparsity in Recommender Systems

3. A network-based drug repurposing method via non-negative matrix factorization

4. NMTF-DTI: A Nonnegative Matrix Tri-factorization Approach with Multiple Kernel Fusion for Drug-Target Interaction Prediction

5. Application of Dimensionality Reduction in Recommender System - A Case Study;Sarwar;Retrieved from the University of Minnesota Digital Conservancy,2000

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