We introduce intelligent web caching algorithms that employ predictive models of web requests; the general idea is to extend the least recently used LRU) policy of web and proxy servers by making it sensitive to web access models extracted from web log data using data mining techniques. Two approaches have been studied in particular, frequent patterns and decision trees. The experimental results of the new algorithms show substantial improvement over existing LRU-basedcachingtechniques,intermsofhitrate.Wedesignedanddevelopedaprototypicalsystem,whichsupports data warehousing of web log data, extraction of data mining models and simulation of the web caching algorithms.
Web log data warehousing and mining for intelligent web caching
Bonchi F;Giannotti F;Manco G;Nanni M;Pedreschi D;Renso C;Ruggieri S
2001
Abstract
We introduce intelligent web caching algorithms that employ predictive models of web requests; the general idea is to extend the least recently used LRU) policy of web and proxy servers by making it sensitive to web access models extracted from web log data using data mining techniques. Two approaches have been studied in particular, frequent patterns and decision trees. The experimental results of the new algorithms show substantial improvement over existing LRU-basedcachingtechniques,intermsofhitrate.Wedesignedanddevelopedaprototypicalsystem,whichsupports data warehousing of web log data, extraction of data mining models and simulation of the web caching algorithms.File | Dimensione | Formato | |
---|---|---|---|
prod_43955-doc_58923.pdf
solo utenti autorizzati
Descrizione: Web log data warehousing and mining for intelligent web caching
Tipologia:
Versione Editoriale (PDF)
Dimensione
627.37 kB
Formato
Adobe PDF
|
627.37 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.