Diagnostic Agents-Types and Applications: A Discussion

Patel, Tarun M.; Patel, Ajay; Patel, Himatkumar V.

doi:10.13005/ojc/280249

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Recommendation Systems In Art Personalization1

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2024

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“…Collaborative filtering analyzes patterns of past user behavior to recommend artworks that similar users like, while content-based filtering recommends art based on the characteristics of artworks the user has expressed interest in. Hybrid models combine both approaches, refining recommendations to provide a more nuanced and personalized art discovery experience [6,7].…”

Section: Recommendation Systems In Art Personalizationmentioning

confidence: 99%

Personalization of Visual Content of Interactive Art in Augmented Reality Based on Individual User Preferences

Kuliahin

2024

CNCS

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Topicality. In connection with the development of AR technologies and their use in interactive art, there is a growing need to develop methods of personalizing visual content, focused on the individual preferences of users. Research methods. Neural collaborative filtering method, generalized matrix factorization method, mood analysis on video. The purpose of the article: Researching the possibilities of improving the personalization of visual content in interactive art by evaluating the emotional reactions of users and their implicit feedback. The results obtained. The application of neural collaborative filtering and generalized matrix factorization to create adapted visual content in interactive art in AR was considered, which will significantly increase the relevance and immersion of users in interactive works. Conclusion. The considered approach can be used to improve immersiveness and personalization during user interaction with interactive art in AR.

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Section: Recommendation Systems In Art Personalizationmentioning

confidence: 99%

Personalization of Visual Content of Interactive Art in Augmented Reality Based on Individual User Preferences

Kuliahin

2024

CNCS

View full text Add to dashboard Cite

show abstract

Diagnostic Agents-Types and Applications: A Discussion

Cited by 1 publication

References 0 publications

Personalization of Visual Content of Interactive Art in Augmented Reality Based on Individual User Preferences

Personalization of Visual Content of Interactive Art in Augmented Reality Based on Individual User Preferences

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