Data Clustering Algorithms and Applications

• Main Authors: Aggarwal, Charu C., Reddy, Chandan K.
• Format: eBook Book
• Language: English
• Published: Boca Raton CRC Press 2014; CRC Press LLC; Chapman & Hall
• Edition: 1
• Series: Chapman & Hall/CRC data mining and knowledge discovery series
• Subjects: Cluster analysis; Data mining; Document clustering; File organization (Computer science); Machine theory; Gene Expression Time Series Data; Data Set; Latent Dirichlet Allocation; High Dimensional Scenario; LDA Model; Internal Validation Measures; Spectral Clustering; Suffix Tree; Subspace Clustering Algorithm; Semisupervised Clustering; NMF Algorithm; Frequent Item Set; NMF; Consensus Clustering; Agglomerative Hierarchical Clustering; Matrix Factorization Methods; High Dimensional Data; Cluster Ensembles; Graph Partitioning; DBSCAN Algorithm; MCL; Clustering Algorithm; UCI Dataset; Subspace Clustering; Agglomerative Hierarchical Clustering Algorithm
• ISBN: 9781466558212; 1466558210
• DOI: 10.1201/9781315373515

In this book, top researchers from around the world cover the entire area of clustering, from basic methods to more refined and complex data clustering approaches. They pay special attention to recent issues in graphs, social networks, and other domains. The book explores the characteristics of clustering problems in a variety of application areas. It also explains how to glean detailed insight from the clustering process--including how to verify the quality of the underlying clusters--through supervision, human intervention, or the automated generation of alternative clusters.