Document - How data mining and machine learning evolved from relational data base to data science

2018

Contribution to book Open Access

How data mining and machine learning evolved from relational data base to data science

Amato G., Candela L., Castelli D., Esuli A., Falchi F., Gennaro C., Giannotti F., Monreale A., Nanni M., Pagano P., Pappalardo L., Pedreschi D., Pratesi F., Rabitti F., Rinzivillo S., Rossetti G., Ruggieri S., Sebastiani F., Tesconi M.

Sentiment analysis Trajectory mining Data mining Text classification Image classification

During the last 35 years, data management principles such as physical and logical independence, declarative querying and cost-based optimization have led to profound pervasiveness of relational databases in any kind of organization. More importantly, these technical advances have enabled the first round of business intelligence applications and laid the foundation for managing and analyzing Big Data today.

Source: A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years, edited by Sergio Flesca, Sergio Greco, Elio Masciari, Domenico Saccà, pp. 287–306, 2018

Metrics

Back to previous page

Cite as

BibTeX entry

@inbook{oai:it.cnr:prodotti:372761,
	title = {How data mining and machine learning evolved from relational data base to data science},
	author = {Amato G. and Candela L. and Castelli D. and Esuli A. and Falchi F. and Gennaro C. and Giannotti F. and Monreale A. and Nanni M. and Pagano P. and Pappalardo L. and Pedreschi D. and Pratesi F. and Rabitti F. and Rinzivillo S. and Rossetti G. and Ruggieri S. and Sebastiani F. and Tesconi M.},
	doi = {10.1007/978-3-319-61893-7_17},
	booktitle = {A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years, edited by Sergio Flesca, Sergio Greco, Elio Masciari, Domenico Saccà, pp. 287–306, 2018},
	year = {2018}
}