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Machine Learning-Based Personalized Recommendation Algorithms and Their Applications book cover

1st Edition

Machine Learning-Based Personalized Recommendation Algorithms and Their Applications

By Chaohui Liu, Lingling Li Copyright 2027
168 Pages 59 B/W Illustrations
by CRC Press

This book introduces innovative machine learning-based algorithms and a prototype system for personalized book recommendations, addressing key challenges such as inefficiency, data sparsity, cold-start issues, and user interest drift. It begins with an overview of machine learning and recommender system theories, followed by the presentation of three algorithms: a frequent itemset mining... Read more

1. Introduction  2. Theoretical Foundations of Machine Learning  3. Theoretical Foundations of Personalized Recommendation Algorithms  4. A Frequent Itemset Mining Algorithm Using a Novel Three-Dimensional Itemset Matrix and Vectors  5. Collaborative Filtering Algorithm Integrating Penalty Factors and Temporal Weighting  6. Collaborative Filtering Algorithm Based on User Attributes and Item Ratings  7. Prototype System for Personalized Book Recommendation  8. Conclusions and Future Work

Biography

Chaohui Liu is a Senior Experimentalist at Zhengzhou University of Aeronautics, China. His research interests focus on artificial intelligence and machine learning.

Lingling Li is Professor, PhD supervisor, and Vice President at Zhengzhou University of Aeronautics, China. Her research focuses on computer vision.

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