DOI: https://doi.org/10.15587/2313-8416.2015.42641

Constructing a graph of connections in clustering algorithm of complex objects

Татьяна Шатовская, Ирина Витальевна Каменева

Abstract


The article describes the results of modifying the algorithm Chameleon. Hierarchical multi-level algorithm consists of several phases: the construction of the count, coarsening, the separation and recovery. Each phase can be used various approaches and algorithms. The main aim of the work is to study the quality of the clustering of different sets of data using a set of algorithms combinations at different stages of the algorithm and improve the stage of construction by the optimization algorithm of k choice in the graph construction of k of nearest neighbors


Keywords


clustering; algorithm Chameleon; graph construction; connectivity; k-nearest neighbors; hierarchical clustering

References


Asuncion, A., Newman, D. J. (2007). UCI Machine Learning Repository. University of California, School of Information and Computer Science, Irvine, CA. Available at: http://www.ics.uci.edu/~mlearn/MLRepository.html

Blake, C. L., Mer, C. J. (2001). UCI repository of machine learning databases. Available at: http://www.ics.uci.edu/~mlearn/ML-Repository.html

Pearson, S., Mont, M., Bramhall, P. (2004). An Adaptive Privacy Management System For Data Repositories. Trusted Systems Laboratory, Hewlett-Packard Laboratories, Bristol, UK. Available at: http://www.hpl.hp.com/techreports/2004/HPL-2004-211.pdf

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Zimmermann, T. (2006). Knowledge Collaboration by Mining Software Repositories. Saarland University, Saarbrucken, Germany. Available at: http://thomas-zimmermann.com/publications/files/zimmermann-kcsd-2006.pdf


GOST Style Citations


1. Asuncion, A. UCI Machine Learning Repository [Electronic resource] / A. Asuncion, D. J. Newman. – University of California, School of Information and Computer Science, Irvine, CA, 2007. – Available at: http://www.ics.uci.edu/~mlearn/MLRepository.html

2. Blake, C. L. UCI repository of machine learning databases [Electronic resource] / C. L. Blake, C. J. Mer. – 2001. – Available at: http://www.ics.uci.edu/~mlearn/ML-Repository.html

3. Pearson, S. An Adaptive Privacy Management System For Data Repositories [Electronic resource] / S. Pearson, M. Mont, P. Bramhall. – Trusted Systems Laboratory, Hewlett-Packard Laboratories, Bristol, UK, 2004. – Available at: http://www.hpl.hp.com/techreports/2004/HPL-2004-211.pdf

4. Cunningham, K. An open repository and analysis tools for fine-grained longitudinal learner data [Electronic resource] / K. Cunningham, R. Kenneth, Koedinger, A. Skogsholm, B. Leber. – Human Computer Interaction Institute, Carnegie Mellon University, 2008. – Available at: http://www.educationaldatamining.org/EDM2008/uploads/proc/16_Koedinger_45.pdf

5. Xie T. JMAPO: mining API usages from open source repositories. [Electronic resource] / T. Xie, J. Pei // Proceedings of the International Workshop on Mining Software Repositories (MSR '06)ACM. – Press, New York. Shanghai, Chinapp, 2006. – P. 54–57. Available at: http://people.engr.ncsu.edu/txie/publications/msr06-mapo.pdf doi: 10.1145/1137983.1137997 

6. Zimmermann, T. Knowledge Collaboration by Mining Software Repositories [Electronic resource] / T. Zimmermann. – Saarland University, Saarbrucken, Germany, 2006. – Available at: http://thomas-zimmermann.com/publications/files/zimmermann-kcsd-2006.pdf







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