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Data clustering : algorithms and applications / edited by Charu C. Aggarwal, Chandan K. Reddy.

Contributor(s): Aggarwal, Charu C [editor of compilation.] | Reddy, Chandan K, 1980- [editor of compilation.]Material type: TextTextSeries: Chapman & Hall/CRC data mining and knowledge discovery seriesPublisher: Boca Raton : Chapman and Hall/CRC, 2014Description: 1 online resource : text file, PDFContent type: text Media type: computer Carrier type: online resourceISBN: 9781466558229 (ebook : PDF)Subject(s): Document clustering | Cluster analysis | Data mining | Machine theory | File organization (Computer science)Genre/Form: Electronic books.Additional physical formats: Print version:: No titleOnline resources: Click here to access online Also available in print format.
Contents:
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 Mohammed 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.
Summary: "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"-- Provided by publisher.
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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 Mohammed 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.

"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"-- Provided by publisher.

Also available in print format.

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