Subscribe Now Subscribe Today
Science Alert
Curve Top
Information Technology Journal
  Year: 2011 | Volume: 10 | Issue: 3 | Page No.: 478-484
DOI: 10.3923/itj.2011.478.484
Facebook Twitter Digg Reddit Linkedin StumbleUpon E-mail

A Survey of Partition based Clustering Algorithms in Data Mining: An Experimental Approach

T. Velmurugan and T. Santhanam

Clustering is one of the most important research areas in the field of data mining. Clustering means creating groups of objects based on their features in such a way that the objects belonging to the same groups are similar and those belonging in different groups are dissimilar. Clustering is an unsupervised learning technique. Data clustering is the subject of active research in several fields such as statistics, pattern recognition and machine learning. From a practical perspective clustering plays an outstanding role in data mining applications in many domains. The main advantage of clustering is that interesting patterns and structures can be found directly from very large data sets with little or none of the background knowledge. Clustering algorithms can be applied in many areas, for instance marketing, biology, libraries, insurance, city-planning, earthquake studies and www document classification. Data mining adds to clustering the complications of very large datasets with very many attributes of different types. This imposes unique computational requirements on relevant clustering algorithms. A variety of algorithms have recently emerged that meet these requirements and were successfully applied to real-life data mining problems. They are subject of this survey. Also, this survey explores the behavior of some of the partition based clustering algorithms and their basic approaches with experimental results.
PDF Fulltext XML References Citation Report Citation
  •    A Fast Evolutionary Algorithm for Automatic Evolution of Clusters
  •    The RFM-based Institutional Customers Clustering: Case Study of a Digital Content Provider
  •    Medical Data Classification with Naive Bayes Approach
  •    A Complete Survey of Duplicate Record Detection Using Data Mining Techniques
How to cite this article:

T. Velmurugan and T. Santhanam, 2011. A Survey of Partition based Clustering Algorithms in Data Mining: An Experimental Approach. Information Technology Journal, 10: 478-484.

DOI: 10.3923/itj.2011.478.484






Curve Bottom