2015 ExploitingDataMiningforAuthenti

• (Arlorio et al., 2015) ⇒ Marco Arlorio, Jean Daniel Coisson, Giorgio Leonardi, Monica Locatelli, and Luigi Portinale. (2015). “Exploiting Data Mining for Authenticity Assessment and Protection of High-Quality Italian Wines from Piedmont.” In: Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2015). ISBN:978-1-4503-3664-2 doi:10.1145/2783258.2788596

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Cited By

• http://scholar.google.com/scholar?q=%222015%22+Exploiting+Data+Mining+for+Authenticity+Assessment+and+Protection+of+High-Quality+Italian+Wines+from+Piedmont
• http://dl.acm.org/citation.cfm?id=2783258.2788596&preflayout=flat#citedby

Quotes

Author Keywords

• Applications; classifier design and evaluation; compliance and fraud; multi-label and multi-class learning

Abstract

This paper discusses the data mining approach followed in a project called TRAQUASwine, aimed at the definition of methods for data analytical assessment of the authenticity and protection, against fake versions, of some of the highest value Nebbiolo-based wines from Piedmont region in Italy. This is a big issue in the wine market, where commercial frauds related to such a kind of products are estimated to be worth millions of Euros. The objective is twofold: to show that the problem can be addressed without expensive and hyper-specialized wine analyses, and to demonstrate the actual usefulness of classification algorithms for data mining on the resulting chemical profiles. Following Wagstaff's proposal for practical exploitation of machine learning (and data mining) approaches, we describe how data have been collected and prepared for the production of different datasets, how suitable classification models have been identified and how the interpretation of the results suggests the emergence of an active role of classification techniques, based on standard chemical profiling, for the assesment of the authenticity of the wines target of the study.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2015 ExploitingDataMiningforAuthenti	Marco Arlorio Jean Daniel Coisson Giorgio Leonardi Monica Locatelli Luigi Portinale			Exploiting Data Mining for Authenticity Assessment and Protection of High-Quality Italian Wines from Piedmont				10.1145/2783258.2788596		2015