BAMBOOK: PERSONALIZED BOOK RECOMMENDATION AND ENGAGEMENT PLATFORM
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Date
2024-04-19
Authors
Nurtayev, Nurzhan
Saiynov, Dias
Shayakhmet, Yeldar
Amanbek, Dauren
Shayakhmet, Shakhnazar
Journal Title
Journal ISSN
Volume Title
Publisher
Nazarbayev University School of Engineering and Digital Sciences
Abstract
In this report we are going to present a developed book recommendation mobile application system “BamBook”. Purpose of BamBook is to address the gap in digital platforms offering comprehensive book recommendations. Our mobile application is powered by Go, Python and Swift programming languages, while utilising Google’s YouTube Retrieval model for recommendation feature, trained on GoodReads dataset. In the process of development, we encountered challenges mostly in choosing, integrating the model, handling extensive datasets and optimising for the iOS platform. Our system architecture was improved and an iterative method was used to overcome these problems. Although our product still needs more improvements in both back and front parts, evaluation from user’s shows that BamBook meets our main objective which is to provide for users an application with easily understandable interface and relevant recommendation.
Description
Keywords
Type of access: Open access, Book Recommendation, Machine Learning model, Mobile application
Citation
Nurtayev, N. (2024). BamBook: Personalized Book Recommendation and Engagement Platform. Nazarbayev University School of Engineering and Digital Sciences