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Enhancing User Experience through Machine Learning-Based Personalized Recommendation Systems: Behavior Data-Driven UI Design
- 1 Parsons School of Design, MFA Design and Technology, NY, USA
- 2 Interactive Telecommunications Program, New York University, NY, USA
- 3 Computer Science, University of Southern California, CA, USA
* Author to whom correspondence should be addressed.
Abstract
The application of artificial intelligence (AI) continues to expand across various industries, especially in enhancing user experience and optimizing business processes. Through deep learning and machine learning algorithms, companies are able to analyze user behavior data and provide personalized recommendations, which effectively improve customer satisfaction and loyalty. This data-driven approach enables businesses to stand out in a highly competitive market. This paper explores the key role of machine learning-based personalized recommendation systems in improving user experience and highlights the importance of behavioral data-driven UI design for business success. Research shows that successful recommendation systems not only rely on advanced technology applications, but also need to deeply understand user needs to optimize user interface design and promote effective user interaction. As technology continues to advance, personalized recommendation systems will become more intelligent, and companies should actively explore these innovative ways to increase user engagement and brand loyalty to achieve sustainable business growth.
Keywords
Personalized recommendation systems, User experience, machine learning, behavioral data, UI design
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Cite this article
Liu,Y.;Xu,Y.;Zhou,S. (2024). Enhancing User Experience through Machine Learning-Based Personalized Recommendation Systems: Behavior Data-Driven UI Design. Applied and Computational Engineering,112,42-46.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 5th International Conference on Signal Processing and Machine Learning
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