Description
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
Coordinators: Masulli Francesco, Petrosino Alfredo, Rovetta Stefano
Language: English
Subjects for Clustering High--Dimensional Data:
Keywords
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
Support: Print on demand
Description
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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
