The huge amount of data, generated by daily-life data sources, represents a big opportunity for the development and advancement in several fields: scientific research, social life and industry. At the same time, analyzing these big repositories is a hard challenge, since the overload of information can overwhelm our capability of reading and understanding data, making finding useful pieces of information a difficult task. In this discussion we give a general overview about Knowledge Discovery in Databases as a scientific discipline that provides methodologies, techniques and tools for dealing with Big Data in order to find underlying knowledge that can be exploited in decision making processes.

Knowledge Discovery in Databases

Massimo Guarascio;Giuseppe Manco;Ettore Ritacco
2018

Abstract

The huge amount of data, generated by daily-life data sources, represents a big opportunity for the development and advancement in several fields: scientific research, social life and industry. At the same time, analyzing these big repositories is a hard challenge, since the overload of information can overwhelm our capability of reading and understanding data, making finding useful pieces of information a difficult task. In this discussion we give a general overview about Knowledge Discovery in Databases as a scientific discipline that provides methodologies, techniques and tools for dealing with Big Data in order to find underlying knowledge that can be exploited in decision making processes.
2018
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR
978-0-12-809633-8
Anomaly detection
Associations rules
Classification
Clustering
CRISP-DM methodology
Data mining
Knowledge discovery
Machine learning
Model evaluation
Pattern recognition
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/345569
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