Survey on Hubness - Based Clustering Algorithms
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064



Downloads: 99

Review Papers | Computer Science & Engineering | India | Volume 3 Issue 10, October 2014

Survey on Hubness - Based Clustering Algorithms

Nikita Dhamal, Antara Bhatttacharya

Clustering of high dimensionality data which can be seen in almost all fields these days is becoming very tedious process. The key disadvantage of high dimensional data which we can pen down is curse of dimensionality. As the magnitude of datasets grows the data points become sparse and density of area becomes less making it difficult to cluster that data which further reduces the performance of traditional algorithms used for clustering. To rout these toils hubness based algorithms were introduced as a variation to the these algorithms which influences the distribution of the data points among the k-nearest neighbor. The hubness is an unguided method which finds out which points appear more frequently in the k-nearest neighbor than other points in the dataset. This paper discuss the ways of clustering algorithms using hubness phenomenon. One of the methods is based on condensed nearest neighbor which is performed iteratively on the order independent data. The next algorithm is hinged for fuzzy based approaches which performs better on uncertain data ie. partially exposed or incomplete data. The proposed algorithms are basically used for increasing the efficiency and increasing predicting accuracy of the system.

Keywords: clustering, high dimensional data, hubness, nearest neighbor

Edition: Volume 3 Issue 10, October 2014

Pages: 2253 - 2256

Share this Article

How to Cite this Article?

Nikita Dhamal, Antara Bhatttacharya, "Survey on Hubness - Based Clustering Algorithms", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=OCT14697, Volume 3 Issue 10, October 2014, 2253 - 2256

Enter Your Email Address




Similar Articles with Keyword 'clustering'

Downloads: 1 | Monthly Hits: ⮙1

Survey Paper, Computer Science & Engineering, India, Volume 10 Issue 5, May 2021

Pages: 948 - 951

Survey on Various Image Segmentation Techniques

Babita Chauhan

Share this Article

Downloads: 1 | Weekly Hits: ⮙1 | Monthly Hits: ⮙1

Research Paper, Computer Science & Engineering, India, Volume 10 Issue 7, July 2021

Pages: 421 - 424

Comparative Analysis of AI Techniques in the Prediction of Heart Disease

Irtiqa Dhar

Share this Article

Similar Articles with Keyword 'high dimensional data'

Downloads: 106

Survey Paper, Computer Science & Engineering, India, Volume 3 Issue 12, December 2014

Pages: 691 - 694

A Survey on Fast Clustering Based Feature Selection Algorithm for High Dimensional Data

Swapnil A. Sutar, Prof. Devendra P. Gadekar

Share this Article

Downloads: 111

Survey Paper, Computer Science & Engineering, India, Volume 3 Issue 6, June 2014

Pages: 679 - 682

Review of Slicing Approach: Data Publishing with Data Privacy and Data Utility

Vina M. Lomte, Hemlata B. Deorukhakar

Share this Article

Similar Articles with Keyword 'hubness'

Downloads: 121

Survey Paper, Computer Science & Engineering, India, Volume 5 Issue 12, December 2016

Pages: 1736 - 1739

Distance-Based Outlier Detection: Reverse Nearest Neighbors approach

Pranita Jawale

Share this Article

Downloads: 130

Survey Paper, Computer Science & Engineering, India, Volume 5 Issue 1, January 2016

Pages: 280 - 282

A Survey On: Distance Based Outlier Detection

Smita Patil, P. D.Chouksey

Share this Article

Similar Articles with Keyword 'nearest neighbor'

Downloads: 502 | Weekly Hits: ⮙1 | Monthly Hits: ⮙8

Research Paper, Computer Science & Engineering, India, Volume 9 Issue 7, July 2020

Pages: 1454 - 1458

Heart Disease Prediction with Machine Learning Approaches

Megha Kamboj

Share this Article

Downloads: 100

Research Paper, Computer Science & Engineering, India, Volume 9 Issue 9, September 2020

Pages: 759 - 761

Empirical Study of Fake Reviews Detection of Online Reviews from E-Commerce Website

Phani K. Cheruku, Atul Kumar

Share this Article



Top