| Description |
1 online resource (xxvi, 620 pages) : illustrations |
| Series |
Chapman & Hall/CRC data mining and knowledge discovery series |
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Chapman & Hall/CRC data mining and knowledge discovery series.
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| 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 [and four others] -- 15. Time-series data clustering / Dimitrios Kotsakos [and three others] -- 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 |
This title covers clustering, from basic methods to more refined and complex data clustering approaches, paying special attention to recent issues in graphs, social networks, and other domains. It presents core methods for data clustering, including probabilistic, density- and grid-based, and spectral clustering and explores various problems and scenarios pertaining to multimedia, text, biological, categorical, network, streams, and uncertain data |
| Notes |
"A Chapman & Hall book." |
| Bibliography |
Includes bibliographical references |
| Notes |
Print version record |
| Subject |
Document clustering.
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Cluster analysis.
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Data mining.
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Machine theory.
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File organization (Computer science)
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Data Mining
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COMPUTERS / Database Management / Data Mining.
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COMPUTERS / Machine Theory.
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characteristics of clustering problems.
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grid-based clustering.
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high-dimensional clustering.
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methods for data clustering.
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spectral clustering.
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variations of the clustering process.
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Cluster analysis
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Data mining
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Document clustering
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File organization (Computer science)
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Machine theory
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| Form |
Electronic book
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| Author |
Aggarwal, Charu C.
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Reddy, Chandan K., 1980-
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| ISBN |
1466558210 |
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9781466558212 |
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9781466558229 |
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1466558229 |
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9781322631028 |
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1322631026 |
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