Data mining started off by finding clearly defined patterns in large sets of relatively homogeneous data. Over the years, increasingly complex data sources were tackled. As a result, newly developed methods grew in complexity, but the basic assumption that the type of pattern sought for was known beforehand remained a constant. I argue that we will ultimately require new systems which enable users to gain new, often surprising insights before they can even determine how to fine-tune and/or validate the patterns themselves
Predictive accuracy claims should give explicit descriptions of the steps followed, with access to t...
Data mining aims at discovering valid, novel and potentially useful patterns from data. Over last tw...
Organizations are taking advantage of "data-mining" techniques to leverage the vast amounts of data ...
International audienceComputer science is essentially an applied or engineering science , creating t...
Data mining (knowledge discovery from data) may be viewed as the extraction of interesting (non-triv...
We consider the problem of discovering descriptive models of large, multidimensional datasets contai...
from classification to pattern mining, reached considerable levels of efficiency, and their extensio...
in a database. For many reasons—encoding errors, measurement errors, unrecorded causes of recorded f...
AbstractData mining is defined as the computational process of analyzing large amounts of data in or...
We live in the era of data and need tools to discover valuable information in large amounts of data....
www-stat.wharton.upenn.edu/~stine Modern data mining combines familiar and novel statistical methods...
Until recently, data analysts would pour over hundreds, maybe even thousands of bits of data looking...
The recent studies of pattern mining have given more attention to discovering patterns that are inte...
Data mining is a complex process that aims to derive an accurate predictive model starting from a co...
We introduce a new kind of patterns, called emerging patterns (EPs), for knowledge discovery from da...
Predictive accuracy claims should give explicit descriptions of the steps followed, with access to t...
Data mining aims at discovering valid, novel and potentially useful patterns from data. Over last tw...
Organizations are taking advantage of "data-mining" techniques to leverage the vast amounts of data ...
International audienceComputer science is essentially an applied or engineering science , creating t...
Data mining (knowledge discovery from data) may be viewed as the extraction of interesting (non-triv...
We consider the problem of discovering descriptive models of large, multidimensional datasets contai...
from classification to pattern mining, reached considerable levels of efficiency, and their extensio...
in a database. For many reasons—encoding errors, measurement errors, unrecorded causes of recorded f...
AbstractData mining is defined as the computational process of analyzing large amounts of data in or...
We live in the era of data and need tools to discover valuable information in large amounts of data....
www-stat.wharton.upenn.edu/~stine Modern data mining combines familiar and novel statistical methods...
Until recently, data analysts would pour over hundreds, maybe even thousands of bits of data looking...
The recent studies of pattern mining have given more attention to discovering patterns that are inte...
Data mining is a complex process that aims to derive an accurate predictive model starting from a co...
We introduce a new kind of patterns, called emerging patterns (EPs), for knowledge discovery from da...
Predictive accuracy claims should give explicit descriptions of the steps followed, with access to t...
Data mining aims at discovering valid, novel and potentially useful patterns from data. Over last tw...
Organizations are taking advantage of "data-mining" techniques to leverage the vast amounts of data ...