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A Comprehensive Guide Through the Italian Database Research Over the Last 25 YearsMatching Techniques for Data Integration and Exploration: From Databases to Big Data

A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years: Matching... [In the last two decades, data matching has been addressed for different purposes and in different application contexts, ranging from data integration, to ontology evolution, to semantic data clouding, until more recent exploratory data analysis over large/big datasets. This paper describes the evolution of research activity on matching techniques for data integration and exploration at the ISLab group of the Università degli Studi di Milano. We analyze the matching techniques according to the structure of target data, the algorithmic pattern of the matching process, and the application focus, and we discuss the results of using our techniques for exploratory analysis of a real dataset composed by all the SEBD proceedings publications in the timeframe 1993–2016.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A Comprehensive Guide Through the Italian Database Research Over the Last 25 YearsMatching Techniques for Data Integration and Exploration: From Databases to Big Data

Part of the Studies in Big Data Book Series (volume 31)
Editors: Flesca, Sergio; Greco, Sergio; Masciari, Elio; Saccà, Domenico

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References (15)

Publisher
Springer International Publishing
Copyright
© Springer International Publishing AG 2018
ISBN
978-3-319-61892-0
Pages
61 –76
DOI
10.1007/978-3-319-61893-7_4
Publisher site
See Chapter on Publisher Site

Abstract

[In the last two decades, data matching has been addressed for different purposes and in different application contexts, ranging from data integration, to ontology evolution, to semantic data clouding, until more recent exploratory data analysis over large/big datasets. This paper describes the evolution of research activity on matching techniques for data integration and exploration at the ISLab group of the Università degli Studi di Milano. We analyze the matching techniques according to the structure of target data, the algorithmic pattern of the matching process, and the application focus, and we discuss the results of using our techniques for exploratory analysis of a real dataset composed by all the SEBD proceedings publications in the timeframe 1993–2016.]

Published: May 31, 2017

Keywords: Matching techniques; Data integration; Data exploration; Big data

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