TEST - Catálogo BURRF
   

Advances in knowledge discovery in databases / Animesh Adhikari, Jhimli Adhikari.

Por: Colaborador(es): Tipo de material: TextoTextoSeries Intelligent Systems Reference Library ; 79Editor: Cham : Springer International Publishing : Springer, 2015Descripción: xv, 370 páginas : 136 ilustracionesTipo de contenido:
  • texto
Tipo de medio:
  • computadora
Tipo de portador:
  • recurso en línea
ISBN:
  • 9783319132129
Formatos físicos adicionales: Edición impresa:: Sin títuloClasificación LoC:
  • Q342
Recursos en línea:
Contenidos:
Introduction -- Synthesizing conditional patterns in a database -- Synthesizing arbitrary Boolean expressions induced by frequent itemsets -- Measuring association among items in a database -- Mining association rules induced by item and quantity purchased -- Mining patterns different related databases -- Mining icebergs in different time-stamped data sources.-Synthesizing exceptional patterns in different data Sources -- Clustering items in time-stamped databases -- Synthesizing some extreme association rules from multiple databases -- Clustering local frequency items in multiple data sources -- Mining patterns of select items in different data sources -- Mining calendar-based periodic patterns in time-stamped data -- Measuring influence of an item in time-stamped databases -- Clustering multiple databases induced by local patterns -- Enhancing quality of patterns in multiple related databases -- Concluding remarks.
Valoración
    Valoración media: 0.0 (0 votos)
No hay ítems correspondientes a este registro

Springer eBooks

Introduction -- Synthesizing conditional patterns in a database -- Synthesizing arbitrary Boolean expressions induced by frequent itemsets -- Measuring association among items in a database -- Mining association rules induced by item and quantity purchased -- Mining patterns different related databases -- Mining icebergs in different time-stamped data sources.-Synthesizing exceptional patterns in different data Sources -- Clustering items in time-stamped databases -- Synthesizing some extreme association rules from multiple databases -- Clustering local frequency items in multiple data sources -- Mining patterns of select items in different data sources -- Mining calendar-based periodic patterns in time-stamped data -- Measuring influence of an item in time-stamped databases -- Clustering multiple databases induced by local patterns -- Enhancing quality of patterns in multiple related databases -- Concluding remarks.

Para consulta fuera de la UANL se requiere clave de acceso remoto.

Universidad Autónoma de Nuevo León
Secretaría de Extensión y Cultura - Dirección de Bibliotecas @
Soportado en Koha