ranked output - translation to English
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ranked output - translation to English

A PROPERTY DESCRIBING RUN-TIME COMPLEXITY OF ALGORITHMS
Output sensitivity; Output-sensitivity

ranked output      
(n.) = resultado ordenado jerárquicamente
Ex: The ranked output also allowed Salton to develop the normalized recall measure used in a modified form by Cleverdon in Cranfield II, and a corresponding normalized precision figure.
ranked         
PROCESS OF ORDERING ITEMS IN A SET BY CRITERIA
Rank order; Ranking system; World ranking; Rankings; Ranked; World Ranking; World rankings; World Rankings; Rank statistics; Second place; Ranking (statistics)
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* in ranked order = en orden jerárquico
* ranked output = resultado ordenado jerárquicamente
* top-ranked = situado en primer lugar, más votado, más prestigioso, preferido
ranking         
PROCESS OF ORDERING ITEMS IN A SET BY CRITERIA
Rank order; Ranking system; World ranking; Rankings; Ranked; World Ranking; World rankings; World Rankings; Rank statistics; Second place; Ranking (statistics)
(n.) = categoría, clasificación, posición, ranking, orden, jerarquía, jerarquización
Ex: Those documents with sufficiently high rankings will be deemed relevant and eventually retrieved.
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* high-ranking = de alto rango
* output ranking = ordenación jerárquica del resultado de la búsqueda
* ranking algorithm = algoritmo de ordenación por pertinencia
* ranking order = jerarquía
* relevance ranking = ordenación por pertinencia, clasificación por pertinencia, coeficiente de pertinencia, índice de pertinencia
* seniority ranking = clasificación por antigüedad

Definition

output
output (ingl.; pronunc. [áutput])
1 m. Econ. Producto resultante de un proceso productivo.
2 Inform. Información que proporciona el ordenador después de procesar los datos. Salida.

Wikipedia

Output-sensitive algorithm

In computer science, an output-sensitive algorithm is an algorithm whose running time depends on the size of the output, instead of, or in addition to, the size of the input. For certain problems where the output size varies widely, for example from linear in the size of the input to quadratic in the size of the input, analyses that take the output size explicitly into account can produce better runtime bounds that differentiate algorithms that would otherwise have identical asymptotic complexity.