Abstract
The artificial intelligence community has done much theorizing about how AI can help with the problem of successful information search in the vast reservoir of knowledge available on the Internet. Deep learning advances in speech recognition, image processing, and natural language processing have gotten much attention recently. Meanwhile, in several recent studies, deep learning is helpful in recommendation systems and information retrieval.
Recommendation systems provide individualized recommendations as a solution to this problem. Among the most common method for predicting these recommendations is content-based. This study employs this method to develop a system that provides more precise book recommendations.
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Samih, A., Ghadi, A., Fennan, A. (2023). Deep Graph Embeddings for Content Based-Book Recommendations. In: Lazaar, M., En-Naimi, E.M., Zouhair, A., Al Achhab, M., Mahboub, O. (eds) Proceedings of the 6th International Conference on Big Data and Internet of Things. BDIoT 2022. Lecture Notes in Networks and Systems, vol 625. Springer, Cham. https://doi.org/10.1007/978-3-031-28387-1_10
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