_Clustering or Cluster analysis is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense) to each other than to those in other groups (clusters). — _Wikipedia

This post contents:

1. Books
2. Research Papers
3. Online Courses and Videos
4. Clustering Datasets
5. List of Journals

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Books

Data Clustering by Chandan K. Reddy and Charu C. Aggarwal. This textbook covers most of the clustering techniques. Highly recommended to people working in clustering.

Data Clustering: Theory, Algorithms, and Applications by Guojun Gan, Chaoqun Ma and Jianhong Wu. This is a useful compendium of a variety of methods of clustering, for a variety of data types, with numerous measures of similarity, and many examples of algorithms. The ultimate emphasis is on the algorithms, even the implementation in MATLAB or C++.

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Research Papers

Survey Papers

Survey of clustering algorithms

A Survey of Clustering Data Mining Techniques

Clustering high-dimensional data: A survey on subspace clustering

A Survey of Text Clustering Algorithms

A Survey of Recent Advances in Hierarchical Clustering Algorithms

Subspace Clustering for High Dimensional Data: A Review

State-of-the-art Methods

DBSCAN

Density-Based Clustering Algorithms

DBSCAN

DENCLUE 2.0

Hierarchical Clustering Algorithms

Subspace Clustering

CLIQUE(Clustering In QUEst)

MAFIA

ENCLUS

P3C

SUBCLU(density-connected Subspace Clustering)

FIRES(FIlter REfinement Subspace clustering)

CSSub (Clustering by Shared Subspaces)

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