International Journal of Information Technology and Computer Science (IJITCS)
IJITCS Vol. 9, No. 3, 8 Mar. 2017
Cover page and Table of Contents: PDF (size: 392KB)
Priority Based New Approach for Correlation Clustering
Full Text (PDF, 392KB), PP.71-79
Views: 0 Downloads: 0
Author(s)
Aaditya Jain
1,*
Suchita Tyagi
2
Index Terms
Clustering Problems, Correlation Clustering, Chromatic Balls, and Priority Based Chromatic Balls
Abstract
Emerging source of Information like social network, bibliographic data and interaction network of proteins have complex relation among data objects and need to be processed in different manner than traditional data analysis. Correlation clustering is one such new style of viewing data and analyzing it to detect patterns and clusters. Being a new field, it has lot of scope for research. This paper discusses a method to solve problem of chromatic correlation clustering where data objects as nodes of a graph are connected through color-labeled edges representing relations among objects. Purposed heuristic performs better than the previous works.
Cite This Paper
Aaditya Jain, Suchita Tyagi, "Priority Based New Approach for Correlation Clustering", International Journal of Information Technology and Computer Science(IJITCS), Vol.9, No.3, pp.71-79, 2017. DOI:10.5815/ijitcs.2017.03.08
Reference
[1]E.W. Forgy, "Cluster Analysis of Multivariate Data: Efficiency v/s Interpretability of Classification", Biometrics, 21, 768-769, 1965.
[2]J. C. Bezdek , R. Ehrlich and W. Full, "FCM: The Fuzzy C-Means Clustering Algorithm" , Computers & Geosciences, vol. 10, No. 2-3, pp. 191 -203, 1984.
[3]N. Bansal, A. Blum and S. Chawla, "Correlation Clustering ", Machine Learning, Vol. 56, Pp. 89-113, 2004.
[4]F. Bonchi, A Gionis , F. Gullo and Ukkonen, " Chromatic Correlation Clustering ", Proceedings of The 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'12) ,pp. 1321-1329,2012.
[5]F. Bonchi, A. Gionis, F. Gullo Charalampos, E. Tsourakakis And A. Ukkonen,"Chromatic Correction Clustering", ACM Transactions on Knowledge Discovery from Data (TKDD),Vol.9 Issue 4 ,No. 34, 2015.
[6]Aaditya Jain, Dr. Bala Buksh, “Advancement in Clustering with the Concept of Correlation Clustering-A Survey”, International Journal of Engineering Development and Research, Vol. 4, Issue 2, 2016.
[7]M. Rice and V. J. Tsotras, “Graph indexing of road networks for shortest path queries with label restrictions”, Proceedings of the VLDB Endowment, Vol. 4, No. 2, pp. 69-80, 2010.
[8]M. J. Kearns, R. E. Schapire, and L. M. Sellie, "Toward Efficient Agnostic Learning ", Machine Learning , Vol. 17, No. 2-3, pp. 115-142, 1994.
[9]I. Giotis and V. Guruswami, “Correlation Clustering with a Fixed Number of Clusters”, Theory Of Computing, Vol. 2, pp. 249–266, 2006.
[10]N. Ailon and E. Liberty, “Correlation Clustering Revisited: The "True" Cost of Error Minimization Problems”, Proceedings of the 36th International Colloquium on Automata, Languages and Programming: Part I (ICALP '09), pp. 24-36, 2009.
[11]Yi Gu and Chaoli Wang, “A Study of Hierarchical Correlation Clustering for Scientific Volume Data”, Advances in Visual Computing, Volume 6455 of the series Lecture Notes in Computer Science, pp 437-446, 2010.
[12]K. Makarychev, Y. Makarychev and A. Vijayaraghavan, “Correlation Clustering with Noisy Partial Information” in JMLR: Workshop and Conference Proceedings, vol 40, pp.1–22, 2015.
[13]Kookjin Ahn, Graham Cormode, Sudipto Guha, Andrew Mcgregor and Anthony Wirth, “Correlation Clustering in Data Streams” in Proceedings of the 32nd International Conference on Machine Learning (ICML-15), pp:2237-2246, 2015.