Part 1: Cross-Domain Conference and Workshop on Multidisciplinary Research and Practice for Information Systems (CD-ARES 2013)International audienceIn this paper, we present a new approach relevant to the discovery of correlated patterns, based on the use of multicore architectures. Our work rests on a full KDD system and allows one to extract Decision Correlation Rules based on the Chi-squared criterion that include a target column from any database. To achieve this objective, we use a levelwise algorithm as well as contingency vectors, an alternate and more powerful representation of contingency tables, in order to prune the search space. The goal is to parallelize the processing associated with the extraction of relevant rules. The paral...
Given a set of data objects, correlation computing refers to the problem of efficiently finding grou...
Increasing variety and affordability of multi- and many-core embedded architectures can pose both a ...
Abstract. To mine databases in which examples are tagged with class labels, the minimum correlation ...
Part 1: Cross-Domain Conference and Workshop on Multidisciplinary Research and Practice for Informat...
Abstract—We present a new approach related to the discovery of correlated patterns based on the use ...
16 pagesInternational audienceIn this paper, we present a new approach relevant to the discovery of ...
In this paper, two concepts are introduced: decision correlation rules and contingency vectors. The ...
International audienceGradual patterns highlight complex order correlations of the form "The more/le...
Data mining is an emerging research area, whose goal is to extract significant patterns or interesti...
In this paper we propose two new parallel formulations of the Apriori algorithm that is used for com...
Data mining is an emerging research area, whose goal is to extract significant patterns or interesti...
The problem of mining hidden associations present in the large amounts of data has seen widespread a...
The amount of data produced by ubiquitous computing applications is quickly growing, due to the perv...
Thesis (Ph. D.)--University of Rochester. Dept. of Computer Science, 1998. Simultaneously published...
We present parallel algorithms for mining Correlated Heavy Hitters from a two-dimensional data strea...
Given a set of data objects, correlation computing refers to the problem of efficiently finding grou...
Increasing variety and affordability of multi- and many-core embedded architectures can pose both a ...
Abstract. To mine databases in which examples are tagged with class labels, the minimum correlation ...
Part 1: Cross-Domain Conference and Workshop on Multidisciplinary Research and Practice for Informat...
Abstract—We present a new approach related to the discovery of correlated patterns based on the use ...
16 pagesInternational audienceIn this paper, we present a new approach relevant to the discovery of ...
In this paper, two concepts are introduced: decision correlation rules and contingency vectors. The ...
International audienceGradual patterns highlight complex order correlations of the form "The more/le...
Data mining is an emerging research area, whose goal is to extract significant patterns or interesti...
In this paper we propose two new parallel formulations of the Apriori algorithm that is used for com...
Data mining is an emerging research area, whose goal is to extract significant patterns or interesti...
The problem of mining hidden associations present in the large amounts of data has seen widespread a...
The amount of data produced by ubiquitous computing applications is quickly growing, due to the perv...
Thesis (Ph. D.)--University of Rochester. Dept. of Computer Science, 1998. Simultaneously published...
We present parallel algorithms for mining Correlated Heavy Hitters from a two-dimensional data strea...
Given a set of data objects, correlation computing refers to the problem of efficiently finding grou...
Increasing variety and affordability of multi- and many-core embedded architectures can pose both a ...
Abstract. To mine databases in which examples are tagged with class labels, the minimum correlation ...