Clustering High--Dimensional Data, 1st ed. 2015 First International Workshop, CHDD 2012, Naples, Italy, May 15, 2012, Revised Selected Papers Information Systems and Applications, incl. Internet/Web, and HCI Series
Coordonnateurs : Masulli Francesco, Petrosino Alfredo, Rovetta Stefano
This book constitutes the proceedings of the International Workshop on Clustering High-Dimensional Data, CHDD 2012, held in Naples, Italy, in May 2012.
The 9 papers presented in this volume were carefully reviewed and selected from 15 submissions. They deal with the general subject and issues of high-dimensional data clustering; present examples of techniques used to find and investigate clusters in high dimensionality; and the most common approach to tackle dimensionality problems, namely, dimensionality reduction and its application in clustering.
Includes supplementary material: sn.pub/extras
Date de parution : 11-2015
Ouvrage de 149 p.
15.5x23.5 cm
Thèmes de Clustering High--Dimensional Data :
Mots-clés :
big data clustering; dimensionality reduction; high dimensional data analysis; machine learning; time series analysis; anomaly detection; cluster analysis; clustering; data mining; efficiency; exploratory data analysis; inductive inference; manifold learning; modeling hierarchies; rank-order statistics; rough fuzzy sets; self-organizing maps; subspace clustering; unsupervised feature selection; unsupervised models of learning
