Title: Data Clustering
Description: "Clustering is a diverse topic, and the underlying algorithms depend greatly on the data domain and problem scenario. This book focuses on three primary aspects of data clustering: the core methods such as probabilistic, density-based, grid-based, and spectral clustering etc; different problem domains and scenarios such as multimedia, text, biological, categorical, network, and uncertain data as well as data streams; and different detailed insights from the clustering process because of the subjectivity of the clustering process, and the many different ways in which the same data set can be clustered"--
Subjects: Cluster analysis, Data mining, Machine theory, File organization (computer science), Document clustering, Regroupement des documents (Informatique), Classification automatique (Statistique), Exploration de données (Informatique), Théorie des automates, Fichiers (Informatique), Organisation