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

Contributor(s): Material type: TextTextSeries: Chapman & Hall/CRC data mining and knowledge discovery seriesPublication details: Boca Raton : CRC Press, c2014.Description: xxvi, 622 p. : illustrations ; 26 cmISBN:
  • 9781466558212 (hardback)
Subject(s): DDC classification:
  • 000SA.072 23 Ag266
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 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.
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.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 000SA.072 Ag266 (Browse shelf(Opens below)) Available 136558
Total holds: 0

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.

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.

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