Un algorithme de fouille de données générique et parallèle pour architecture multi-coeurs

Abstract : In the pattern mining field, there exist a large number of algorithms that can solve a large variety of distinct but similar pattern mining problems. This variety prevent broad adoption of data analysis with pattern mining algorithms. In this thesis we propose a formal framework that is able to capture a broad range of pattern mining problems. We illustrate the generality of our framework by formalizing three different pattern mining problems: the problem of closed frequent itemset mining, the problem of closed relational graph mining and the problem of closed gradual itemset mining. Building on this framework, we have designed ParaMiner, a generic and parallel algorithm for pattern mining. ParaMiner is able to solve any pattern mining problem that can be formalized within our framework. In order to achieve practical efficiency we have generalized important optimizations from state of the art algorithms and we have made ParaMiner able to exploit parallel computing platforms. We have conducted thorough experiments that demonstrate that despite being a generic algorithm, ParaMiner can compete with the fastest ad-hoc algorithms.
Document type :
Theses
Liste complète des métadonnées

Cited literature [58 references]  Display  Hide  Download

https://tel.archives-ouvertes.fr/tel-00680025
Contributor : Abes Star <>
Submitted on : Saturday, March 17, 2012 - 10:02:26 AM
Last modification on : Friday, April 19, 2019 - 1:37:50 AM
Document(s) archivé(s) le : Monday, June 18, 2012 - 5:02:20 PM

File

negrevergne_benjamin_2011_arch...
Version validated by the jury (STAR)

Identifiers

  • HAL Id : tel-00680025, version 1

Collections

Citation

Benjamin Negrevergne. Un algorithme de fouille de données générique et parallèle pour architecture multi-coeurs. Autre [cs.OH]. Université Grenoble Alpes, 2011. Français. ⟨NNT : 2011GRENM062⟩. ⟨tel-00680025⟩

Share

Metrics

Record views

1236

Files downloads

736