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Symbolic data analysis

Known as: SDA 
Symbolic data analysis (SDA) is an extension of standard data analysis where symbolic data tables are used as input and symbolic objects are… 
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Papers overview

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Highly Cited
2017
Highly Cited
2017
The stochastic gradual descent method (SGD) is a popular optimization technique based on updating each θk parameter in the ∂J… 
2016
2016
Data Science, considered as a science by itself, is in general terms, the extraction of knowledge from data. Symbolic data… 
Highly Cited
2014
Highly Cited
2014
This article studies the impact of ownership structure and capital structure on firms’ financial performance in context of an… 
Highly Cited
2011
Highly Cited
2011
This paper introduces symbolic data analysis, explaining how it extends the classical data models to take into account more… 
2010
2010
The SDA (Spectral Dynamics Analysis) - method (method of THz spectrum dynamics analysis in THz range of frequencies) is used for… 
Highly Cited
2008
Highly Cited
2008
Symbolic data analysis is a relatively new field that provides a range of methods for analyzing complex datasets. Standard… 
Highly Cited
2004
Highly Cited
2004
Exploiting unannotated natural language data is hard largely because unsupervised parameter estimation is hard. We describe… 
Review
2003
Review
2003
The data descriptions of the units are called "symbolic" when they are more complex than standard ones, due to the fact that they… 
1995
1995
We propose an extension of the notion of the histogram used for variables to describe a knowledge base where the knowledge is…