A Survey of Clustering Techniques

Clustering can be considered the most important unsupervised learning technique; so, as every other problem of this kind, it deals with finding a structure in a collection of unlabeled data. Clustering is "the process of organizing objects into groups whose members are similar in some way." A cluster is therefore a collection of objects which are "similar" between them and are "dissimilar" to the objects belonging to other clusters. In this paper, we are describing the clustering techniques and algorithms used for it.

[1]  Paul S. Bradley,et al.  k-Plane Clustering , 2000, J. Glob. Optim..

[2]  Nualsawat Hiransakolwong,et al.  Unsupervised Image Segmentation Using Automated Fuzzy c-Means , 2007, 7th IEEE International Conference on Computer and Information Technology (CIT 2007).

[3]  Jay A. Farrell,et al.  A C-means clustering based fuzzy modeling method , 2000, Ninth IEEE International Conference on Fuzzy Systems. FUZZ- IEEE 2000 (Cat. No.00CH37063).

[4]  Arie van Deursen,et al.  Identifying aspects using fan-in analysis , 2004, 11th Working Conference on Reverse Engineering.

[5]  Grigoreta Sofia Moldovan,et al.  Aspect Mining using a Vector-Space Model Based Clustering Approach , 2006 .

[6]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[7]  Mariano Ceccato,et al.  Aspect mining through the formal concept analysis of execution traces , 2004, 11th Working Conference on Reverse Engineering.

[8]  Pavel Berkhin,et al.  Learning Simple Relations: Theory and Applications , 2002, SDM.

[9]  Gour C. Karmakar,et al.  Object Based Image Segmentation Using Fuzzy Clustering , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[10]  Ran El-Yaniv,et al.  On feature distributional clustering for text categorization , 2001, SIGIR '01.

[11]  B. Sheela Rani,et al.  Colour image segmentation using fuzzy clustering techniques and competitive neural network , 2011, Appl. Soft Comput..

[12]  Bernhard E. Boser,et al.  A training algorithm for optimal margin classifiers , 1992, COLT '92.

[13]  Soumajit Pramanik,et al.  Dynamic Image Segmentation using Fuzzy C-Means based Genetic Algorithm , 2011 .

[14]  Amin Barari,et al.  A Novel Pixon-Based Image Segmentation Process Using Fuzzy Filtering and Fuzzy C-mean Algorithm , 2011 .

[15]  Prabhakar Raghavan,et al.  Using Taxonomy, Discriminants, and Signatures for Navigating in Text Databases , 1997, VLDB.

[16]  Andrew McCallum,et al.  Distributional clustering of words for text classification , 1998, SIGIR '98.

[17]  Bor-Chen Kuo,et al.  A Novel Fuzzy Weighted C-Means Method for Image Classification , 2008 .