TY - BOOK AU - Aggarwal,Charu C. AU - Reddy,Chandan K. TI - Data clustering: algorithms and applications T2 - Chapman & Hall/CRC data mining and knowledge discovery series SN - 9781466558212 (hardback) U1 - 000SA.072 23 PY - 2014/// CY - Boca Raton PB - CRC Press KW - Document clustering KW - Cluster analysis KW - Data mining KW - Machine theory KW - File organization (Computer science) N1 - Includes bibliographical references and index; 1. An introduction to cluster analysis / Charu C. Aggarwal -- 2. Feature selection for clustering: a review / Salem Alelyani, Jiliang Tang, and Huan Liu -- 3. Probabilistic models for clustering / Hongbo Deng and Jiawei Han -- 4. A survey of partitional and hierarchical clustering algorithms / Chandan K. Reddy and Bhanukiran Vinzamuri -- 5. Density- Based Clustering / Martin Ester -- 6. Grid-based clustering / Wei Cheng, Wei Wang, and Sandra Batista -- 7. Nonnegative matrix factorizations for clustering: a survey / Tao Li and Chris Ding -- 8. Spectral clustering / Jialu Liu and Jiawei Han -- 9. Clustering high-dimensional data / Arthur Zimek -- 10. A survey of stream clustering algorithms / Charu C. Aggarwal -- 11. Big data clustering / Hanghang Tong and U Kang -- 12. Clustering categorical data / Bill Andreopoulos -- 13. Document clustering: the next frontier / David C. Anastasiu, Andrea Tagarelli, and George Karypis -- 14. Clustering multimedia data / Shen-Fu Tsai, Guo-Jun Qi, Shiyu Chang, Min-Hsuan Tsai, and Thomas S. Huang -- 15. Time-series data clustering / Dimitrios Kotsakos, Goce Trajcevski, Dimitrios Gunopulos, and Charu C. Aggarwal -- 16. Clustering biological data / Chandan K. Reddy, Mohammad Al Hasan, and Mohammad J. Zaki -- 17. Network clustering / Srinivasan Parthasarathy and S M Faisal -- 18. A survey of uncertain data clustering algorithms / Charu C. Aggarwal -- 19. Concepts of visual and interactive clustering / Alexander Hinneburg -- 20. Semisupervised clustering / Amrudin Agovic and Arindam Banerjee -- 21. Alternative clustering analysis: a review / James Bailey -- 22. Cluster ensembles: theory and applications / Joydeep Ghosh and Ayan Acharya -- 23. Clustering validation measures / Hui Xiong and Zhongmou Li -- 24. Educational and software resources for data clustering / Charu C. Aggarwal and Chandan K. Reddy -- Index N2 - 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 ER -