Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches. It pays special attention to recent issues in graphs, social networks, and other domains.
The book focuses on three primary aspects of data clustering:
In this book, top researchers from around the world explore the characteristics of clustering problems in a variety of application areas. They also explain 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.
An Introduction to Cluster Analysis Charu C. Aggarwal
Feature Selection for Clustering: A Review Salem Alelyani, Jiliang Tang, and Huan Liu
Probabilistic Models for Clustering Hongbo Deng and Jiawei Han
A Survey of Partitional and Hierarchical Clustering Algorithms Chandan K. Reddy and Bhanukiran Vinzamuri
Density-Based Clustering Martin Ester
Grid-Based Clustering Wei Cheng, Wei Wang, and Sandra Batista
Non-Negative Matrix Factorizations for Clustering: A Survey Tao Li and Chris Ding
Spectral Clustering Jialu Liu and Jiawei Han
Clustering High-Dimensional Data Arthur Zimek
A Survey of Stream Clustering Algorithms Charu C. Aggarwal
Big Data Clustering Hanghang Tong and U. Kang
Clustering Categorical Data Bill Andreopoulos
Document Clustering: The Next Frontier David C. Anastasiu, Andrea Tagarelli, and George Karypis
Clustering Multimedia Data Shen-Fu Tsai, Guo-Jun Qi, Shiyu Chang, Min-Hsuan Tsai, and Thomas S. Huang
Time Series Data Clustering Dimitrios Kotsakos, Goce Trajcevski, Dimitrios Gunopulos, and Charu C. Aggarwal
Clustering Biological Data Chandan K. Reddy, Mohammad Al Hasan, and Mohammed J. Zaki
Network Clustering Srinivasan Parthasarathy and S.M. Faisal
A Survey of Uncertain Data Clustering Algorithms Charu C. Aggarwal
Concepts of Visual and Interactive Clustering Alexander Hinneburg
Semi-Supervised Clustering Amrudin Agovic and Arindam Banerjee
Alternative Clustering Analysis: A Review James Bailey
Cluster Ensembles: Theory and Applications Joydeep Ghosh and Ayan Acharya
Clustering Validation Measures Hui Xiong and Zhongmou Li
Educational and Software Resources for Data Clustering Charu C. Aggarwal and Chandan K. Reddy
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