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Intelligent Course Recommendation: A Hybrid Deep Learning Perspective

By Kolli, Chandra Sekhar

Product Image: Intelligent Course Recommendation: A Hybrid Deep Learning Perspective

Intelligent Course Recommendation: A Hybrid Deep Learning Perspective

By Kolli, Chandra Sekhar

0 - Default Title
Description
In an era where educational choices can overwhelm students, HHFHNet emerges as a groundbreaking solution for precise course recommendations. This comprehensive guide introduces readers to the innovative Hybrid HAN HDLTex Forward Harmonic Net (HHFHNet) architecture, a sophisticated system that combines the power of Hierarchical Attention Networks (HAN) and Hierarchical Deep Learning for Texts (HDLTex). Through detailed exploration of Term Frequency-Inverse Document Frequency (TF-IDF), ranking-based recommendations, and Explainable Artificial Intelligence (XAI), readers will master the intricacies of building intelligent course recommendation systems. The book presents a novel approach to educational guidance, incorporating content-based filtering, collaborative filtering, and hybrid methods to address the challenging cold-start problem. Whether you're an AI researcher, educational technologist, or academic institution developer, this essential resource provides the theoretical foundation and practical implementation strategies needed to revolutionize course selection processes.
Product details
Binding:
Paperback
Number of Pages:
64
Release Date:
2025-04-24
Publication Date:
2025-04-24
Publisher:
LAP LAMBERT Academic Publishing
Languages:
Original: English
ISBN10:
6208440963
ISBN13:
9786208440961
GPSR Manufacturer Reference:
[email protected]
Weight:
113 g
Height:
150 cm
Width:
220 cm
Thickness:
4 cm
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