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Artificial intelligence-based recommendation system using cloud technologies

Authors: Sulima, Ivan;

Artificial intelligence-based recommendation system using cloud technologies

Abstract

Bachelor thesis: 85 p., 20 figures, 6 tables, 40 references, 1 appendix. The object of research is development of architecture on top of the cloud that uses recommendation mechanisms. The subject of research are a methods and technologies that are used in cloud architection and recommender systems. The aim of the work is to build a system (architecture) using cloud technologies, in the center of which will be a recommendation system. The relevance of this work is associated with possibility of great impact on products revenue with help of personalized recommendations. The research keeps attention on the challenge of developing a recommendation system and predicting user preferences, with a specific focus on utilizing the Cloud technologies. This involves justifying the use of particular methods, tools, and the Cloud development environments, preparing and analyzing the initial dataset, preprocessing raw data, and developing mathematical models tailored to the recommendation problem. The final solution is implemented on AWS using Personalize and then the results are analyzed. Experiments and comparisons with existing approaches are conducted to evaluate the effectiveness of the recommendation system developed on AWS. The experimental results demonstrate the advantages of the Cloud deployment and Recommender systems in general.

Country
Ukraine
Keywords

recommender system, aws, service architecture, колаборативна фільтрація, сервісна архітектура, colaborative filtering, хмарні технології, personalize, рекомендаційна система, cloud technologies

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green