Designing (more) Personalized Music Recommendation Systems: An Architecture for Integrating Interaction Context and User Experience

Designing (more) Personalized Music Recommendation Systems: An Architecture for Integrating Interaction Context and User Experience | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Designing (more) Personalized Music Recommendation Systems: An Architecture for Integrating Interaction Context and User Experience Wililan Assuncao, Marcelo S. Pimenta, Luciana Zaina This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6718785/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Music recommender systems are pivotal to streaming platforms, yet personalization typically relies on listening histories, overlooking context, and user experience. This gap motivates our research objective: to design an architecture that integrates contextual inputs, such as user activity, and explicit UX feedback into the recommendation process. We introduce UConteXt Arch, an architecture layered with Interface, Middleware, Service, and Data tiers that capture context and feedback, and adapt recommendation models. We implemented UConteXt Arch in MixFy, a proof-of-concept Flutter application integrated with Spotify’s Web API to demonstrate feasibility. We conducted two evaluations: a semiotic inspection with eight participants to verify interpretation of context-aware recommendations and refine interface elements. A five-day longitudinal study with 44 participants using the UX Curve and the Technology Acceptance Model measures to assess acceptance and impact. Results show clear user understanding of context adaptations, significant increases in perceived usefulness, ease of use, and intention to continue use, alongside music discovery aligned with user activities. These findings confirm that embedding contextual sensing and UX-driven feedback within a unified architecture enhances recommendation relevance and user engagement, providing a foundation for future research on context-aware recommender systems. Music Recommender Systems User experience Context Context-Aware Full Text Additional Declarations No competing interests reported. Ethics approval and consent to participate: The user studies reported in the manuscript — including both the semiotic evaluation and the five-day longitudinal study with human participants — were conducted in accordance with ethical research guidelines. The research was approved by the Research Ethics Committee of the Federal University of São Carlos (UFSCar), Brazil, under opinion number 6.049.031 and CAAE 66650523.4.0000.5504. All participants provided informed consent before participating in the study. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6718785","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":461006790,"identity":"3ead7053-ae68-44ab-9773-ba4378753c6c","order_by":0,"name":"Wililan Assuncao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAy0lEQVRIiWNgGAWjYBADfn4QmVBAghbJmQ0gLQakaNlwAEQRo8Xg/OIHzIV7bCSMz69O/PDAgEGeX+wAAS03nhkwz3iWJmF24+1mCaDDDGfOTsCvxezGAQNmngOH68xunN0A0pJgcJugluMfQFokjGec3fyDOC3ne8C2SBjw924jzhb7GzwFh2ccSJOQuMG7zSLBQIKwXyT7j298XHDARoK//+zmmz8qbOT5pQloYZBIYDgMY4BIAspBgP8AAzOMMQpGwSgYBaMAKwAAklNG9tHmVxEAAAAASUVORK5CYII=","orcid":"","institution":"Federal University of São Carlos","correspondingAuthor":true,"prefix":"","firstName":"Wililan","middleName":"","lastName":"Assuncao","suffix":""},{"id":461006791,"identity":"f366826a-17bc-4797-aa35-687c2156eb02","order_by":1,"name":"Marcelo S. 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