De fotos a lugares: Generación de itinerarios turísticos personalizados con modelos de lenguaje largo y análisis de imágenes

dc.contributor.advisorGalpin, Ixent
dc.creatorBermejo Xiao, Kenny Andres
dc.date.accessioned2025-06-12T14:35:19Z
dc.date.available2025-06-12T14:35:19Z
dc.date.created2025-05-16
dc.description.abstractEste artículo presenta el desarrollo de una aplicación orientada a la generación automática de itinerarios de viaje personalizados mediante la integración de dos tecnologías emergentes en el campo de la inteligencia artificial: grandes modelos de lenguaje (LLM) y sistemas de reconocimiento de imágenes. La propuesta captura las preferencias del usuario mediante dos mecanismos: (i) un formulario estructurado para la recopilación explícita de intereses, y (ii) el análisis de una imagen proporcionada por el usuario, de la cual se infieren implícitamente las preferencias. La arquitectura del sistema se basa en la combinación de múltiples servicios de inteligencia artificial a través de API, incluyendo servicios de interpretación de imágenes, servicios basados ​​en la localización para identificar sitios turísticos relevantes y modelos de lenguaje para la generación contextual de descripciones y sugerencias. Esta integración permite la construcción de recomendaciones de viaje que consideran tanto las restricciones logísticas (como la duración del vuelo) como los intereses específicos del usuario, presentando así un itinerario visualmente enriquecido y personalizado. La aplicación se evaluó mediante un cuestionario adaptado de la Escala de Usabilidad del Sistema (SUS), obteniendo una puntuación media de 77,59 sobre 100. Este resultado indica un alto nivel de aceptación y usabilidad por parte de los usuarios, lo que respalda la eficacia del sistema como herramienta inteligente de recomendación de viajes.spa
dc.description.abstractenglishThis paper presents the development of an application aimed at the automatic generation of personalized travel itineraries through the integration of two emerging technologies in the field of artificial intelligence: large language models (LLMs) and image recognition systems. The proposal captures user preferences through two mechanisms: (i) a structured form for the explicit collection of interests, and (ii) the analysis of an image provided by the user, from which preferences are implicitly inferred. The system architecture is based on the combination of multiple artificial intelligence services through APIs, including image interpretation services, location-based services for identifying relevant tourist sites, and language models for the contextual generation of descriptions and suggestions. This integration enables the construction of travel recommendations that consider both logistical constraints (such as flight duration) and the user’s specific interests, ultimately presenting a visually enriched and personalized itinerary. The application was evaluated through a questionnaire adapted from the System Usability Scale (SUS), obtaining an average score of 77.59 out of 100. This result indicates a high level of user acceptance and usability, supporting the effectiveness of the system as an intelligent travel recommendation tool.spa
dc.format.extent18 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.identifier.urihttps://hdl.handle.net/20.500.12010/36826
dc.language.isoengspa
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dc.subjectItinerarios de viaje personalizadosspa
dc.subjectModelos de Lenguaje Largospa
dc.subjectReconocimiento de imágenesspa
dc.subjectSistemas de recomendaciónspa
dc.subjectEvaluación de usabilidad (SUS)spa
dc.subject.keywordPersonalized travel itinerariesspa
dc.subject.keywordLarge Language Modelsspa
dc.subject.keywordImage recognitionspa
dc.subject.keywordRecommender systemsspa
dc.subject.keywordUsability evaluation (SUS)spa
dc.subject.lembPlanificación de viajes - Aplicaciones de inteligencia artificial
dc.subject.lembSistemas de recomendación (Informática)
dc.subject.lembProcesamiento de imágenes digitales - Aplicaciones en turismo
dc.titleDe fotos a lugares: Generación de itinerarios turísticos personalizados con modelos de lenguaje largo y análisis de imágenesspa
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1spa

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