Modelo para la recuperación de información con expansión de consulta y perfil de preferencia de los usuarios
Resumen
Comprender la intención de búsqueda del usuario permite identificar y extraer los resultados de búsqueda más relevantes y personalizados de la información disponible según sus necesidades. En el presente artículo se plantea un algoritmo para la recuperación de información relevante que combina las preferencias del perfil del usuario y la expansión de consulta para obtener resultados de búsqueda relevantes y personalizados. El proceso de recuperación de información se valida mediante las métricas de Precision, Recall y Mean Average Precision (MAP) aplicadas a un conjunto de datos que contiene los documentos estandarizados y los perfiles de preferencias. Los resultados permitieron demostrar que el algoritmo mejora el proceso de recuperación de información al arrojar documentos con mejor calidad y relevancia según las necesidades de los usuarios.
Palabras clave
Recuperación de información personalizada, expansión de consulta, perfil de usuario, anotación semántica
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