Metadata, the undiscovered treasure box for book recommender systems for children

What traits can be inferred from book’s descriptive and structural metadata which could support the designers of books recommender systems for children?

Bachelor thesis (2023)

Authors

M.A. Alkhiami Electrical Engineering, Mathematics and Computer Science

Contributors

M.S. Pera Web Information Systems - EEMCS (supervisor 1)
Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright: © 2023 Mohamad awab Alkhiami
Metadata Recommender system Children Readding Trait
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Published Date

03-02-2023

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

This study examines traits that may be derived from book metadata and identifies statistically signifi- cant patterns and trends in order to assist recom- mender system designers for children’s books in selecting the most important traits to take into ac- count. This research focuses on descriptive such as publish year and structural metadata such as the chapters’ count. We rely on data from two different data sets, Goodreads and Wikisource.
The findings of this study, such as the fact that there is a relationship between the number of pages and the reader’s age, may have an impact on the design of recommender systems for children’s books.
This is all with the respect to the fact that children are a vulnerable audience, making it challenging to not infringe on their privacy while gathering infor- mation that can be used in statistical experiments in many fields such as education and health.