Fast Ant-Inspired Clustering Algorithm for Web Usage Mining - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2006

Fast Ant-Inspired Clustering Algorithm for Web Usage Mining

Résumé

In this paper, we propose a new agglomerative clustering algorithm named Leader Ant (LA) that improves the classical Leader clustering algorithm model [14] with a metaphor inspired by the chemical recognition system of ants. In our approach, each object of the data set is associated to the colonial odour of an artificial ant. At each iteration , a randomly chosen ant meets ants from each already existing nest to decide if it integrates this nest or if it creates its own nest. At the end of this iterative meeting process , the nests represent a partition of the intial data set. Similarily to the Leader algorithm, LA processes each data only once, which allows short computation times even on large data sets. LA is compared to other clustering algorithm such as k-means or AntClust [9] on artificial and real data sets. Finally, we briefly describe results obtained when applying LA on real Web usage data from a French museum Web site.
Fichier principal
Vignette du fichier
618.pdf (143.02 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01144862 , version 1 (22-04-2015)

Identifiants

  • HAL Id : hal-01144862 , version 1

Citer

Nicolas Labroche. Fast Ant-Inspired Clustering Algorithm for Web Usage Mining. IPMU 2006 - 11th International Conference on Information Processing and Management of Uncertainty, Jul 2006, Paris, France. pp.2668-2675. ⟨hal-01144862⟩
177 Consultations
242 Téléchargements

Partager

Gmail Facebook X LinkedIn More