Evaluating the Performance of Different Models for Children’s Book Recommendations

Bachelor Thesis (2023)
Author(s)

Z. Qiu (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

M.S. Pera – Mentor (TU Delft - Web Information Systems)

W.P. Brinkman – Graduation committee member (TU Delft - Interactive Intelligence)

Faculty
Electrical Engineering, Mathematics and Computer Science
More Info
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Publication Year
2023
Language
English
Graduation Date
03-02-2023
Awarding Institution
Delft University of Technology
Project
['CSE3000 Research Project']
Programme
['Computer Science and Engineering']
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

Recently, a few children-centered recommendation systems have been created and evaluated. How- ever, these systems required user interaction to cre- ate ground truth to evaluate the result. This research aims to compare some of the traditional recommen- dation models and explore which trait could impact the recommendation process most for different age group users. The result shows the children friendly model does not achieve higher accuracy than the traditional recommendation model. But the book length model and emotion analysis model shows the potential of a good RS that can help children choose books, and cover image recommendation models are only working with younger age

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