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Architectural Proposal for a Hybrid Recommender Engine for Accessible Educational Content

dc.creatorJiménez Martínez, Luis Daviden
dc.creatorÁlvarez Rodríguez, Francisco Javieren
dc.date2026-06-30
dc.date.accessioned2026-08-03T16:43:31Z
dc.date.available2026-08-03T16:43:31Z
dc.identifierhttps://imjeta.org/index.php/IMJETA/article/view/Hybrid-Recommender-Engine-for-Accessible-Educational-Content
dc.identifier10.67294/ayj6b114
dc.identifier.urihttp://bdigital2.ula.ve:8080/xmlui/654321/26932
dc.descriptionThis paper presents an architectural proposal for a modular and adaptive hybrid recommender system designed to improve equitable access to PDF-based educational content for students with visual impairments. The system overcomes the limitations of traditional recommenders, which optimize rankings solely by thematic relevance while ignoring format-related barriers, by implementing a closed-loop approach that prioritizes technical accessibility prior to ranking the educational material. The architecture is structured into four independent layers: automated ingestion via multimodal artificial intelligence, dynamic student profiling, a sequential hybrid recommendation engine, and a semantic presentation interface. The technical viability of the proposal was successfully validated through a functional Python prototype integrated with the Gemini 2.5 Flash model from Google AI Studio, evaluating a repository of real-world documents split between the fields of algebra and programming. Experimental results demonstrated that the system accurately resolves the cold-start problem through an initial technical questionnaire and effectively mitigates the occurrence of false positives in practice, thanks to a reverse feedback loop that automatically updates functional security profiles and restricts resources reported with access flaws.en
dc.formatapplication/pdf
dc.languageen
dc.publisherGrupo Afronta C.A.en
dc.relationhttps://imjeta.org/index.php/IMJETA/article/view/Hybrid-Recommender-Engine-for-Accessible-Educational-Content/19
dc.rightsCopyright (c) 2026 Luis David Jiménez Martínez, Francisco J. Álvarez Rodríguez (Author)en
dc.rightshttps://creativecommons.org/licenses/by-nc-nd/4.0en
dc.sourceInternational Multidisciplinary Journal of Emerging Technologies and Applications; Vol. 1 No. 3 (2026); 68-78en
dc.source3135-6214
dc.subjectInclusive Recommender Systemen
dc.subjectDigital Accessibilityen
dc.subjectVisual Impairmenten
dc.subjectArtificial Intelligenceen
dc.subjectAccessible Educational Contenten
dc.titleArchitectural Proposal for a Hybrid Recommender Engine for Accessible Educational Contenten
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


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