Semantic distillation: a method for clustering objects by their contextual specificity - Archive ouverte HAL Accéder directement au contenu
Chapitre D'ouvrage Année : 2008

Semantic distillation: a method for clustering objects by their contextual specificity

Résumé

Techniques for data-mining, latent semantic analysis, contextual search of databases, etc.\ have long ago been developed by computer scientists working on information retrieval (IR). Experimental scientists, from all disciplines, having to analyse large collections of raw experimental data (astronomical, physical, biological, etc.) have developed powerful methods for their statistical analysis and for clustering, categorising, and classifying objects. Finally, physicists have developed a theory of quantum measurement, unifying the logical, algebraic, and probabilistic aspects of queries into a single formalism. The purpose of this paper is twofold: first to show that when formulated at an abstract level, problems from IR, from statistical data analysis, and from physical measurement theories are very similar and hence can profitably be cross-fertilised, and, secondly, to propose a novel method of fuzzy hierarchical clustering, termed \textit{semantic distillation} --- strongly inspired from the theory of quantum measurement ---, we developed to analyse raw data coming from various types of experiments on DNA arrays. We illustrate the method by analysing DNA arrays experiments and clustering the genes of the array according to their specificity.
Fichier principal
Vignette du fichier
semantic-distillation-sicily.pdf (130.15 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-00177059 , version 1 (05-10-2007)
hal-00177059 , version 2 (06-10-2007)

Identifiants

Citer

Thomas Sierocinski, Antony Le Béchec, Nathalie Théret, Dimitri Petritis. Semantic distillation: a method for clustering objects by their contextual specificity. Krasnogor, N; Nicosia, G; Pavone, M; Pelta, D. Nature inspired cooperative strategies for optimization (NICSO 2007), SPRINGER, pp.431-442, 2008, Studies in computational intelligence. ⟨hal-00177059v2⟩
278 Consultations
209 Téléchargements

Altmetric

Partager

Gmail Mastodon Facebook X LinkedIn More