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Tesi etd-11242009-124601


Thesis type
Tesi di dottorato di ricerca
Author
GROSSI, VALERIO
URN
etd-11242009-124601
Title
A New Framework for Data Streams Classification
Settore scientifico disciplinare
INF/01
Corso di studi
INFORMATICA
Commissione
tutor Prof. Turini, Franco
Parole chiave
  • knowledge discovery
  • data mining
  • data streams
  • classification
Data inizio appello
10/12/2009;
Consultabilità
parziale
Data di rilascio
10/12/2049
Riassunto analitico
Mining data streams has recently become an important and challenging task for a wide range of applications, including sensor networks and web applications. The massive quantity of streaming data coupled with concept drifting are two crucial issues in mining data streams. This thesis proposes a new framework for data streams classification, introducing two distinct structures to face the problem of data management and mining. On the one hand, our approach provides a synthetic structure which maximizes data availability, guaranteeing a single data access. On the other, given the synthetic structure, a selective ensemble of classifiers is managed through time to provide a good prediction accuracy. Both components are designed to maximize data usage and accuracy even in the presence of concept drifting, providing a good trade-off between data access management and quality of the model.
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