Path Clustering: Grouping in an Efficient Way Complex Data Distributions
R. Q. A. Fernandes1, W. A. Pinheiro1,2,3, G. B. Xexéo3, J. M. de Souza3
1 Centro de Desenvolvimento de Sistemas, SMU, Brasília, DF, CEP, Brazil
2 Instituto Militar de Engenharia, Praia Vermelha, Urca, Rio de Janeiro, RJ, CEP, Brazil
3 COPPE/UFRJ, Universidade Federal do Rio de Janeiro, RJ, PO Box 68.501, Brazil
E-mail: ricardo@cds.eb.mil.br, awallace@cos.ufrj.br, xexeo@cos.ufrj.br, jano@cos.ufrj.br
Abstract: This work proposes an algorithm that uses paths based on tile segmentation to build complex clusters. After allocating data items (points) to geometric shapes in tile format, the complexity of our algorithm is related to the number of tiles instead of the number of points. The main novelty is the way our algorithm goes through the grids, saving time and providing good results. It does not demand any configuration parameters from users, making easier to use than other strategies. Besides, the algorithm does not create overlapping clusters, which simplifies the interpretation of results.
Research Paper Link: http://dspace.chitkara.edu.in/jspui/bitstream/123456789/703/3/4-%20Path%20Clustering%20in%20a%20efficient%20way%20complex%20data%20-%20Fernandes.pdf
DOI: https://doi.org/10.15415/jotitt.2017.52004
1 Centro de Desenvolvimento de Sistemas, SMU, Brasília, DF, CEP, Brazil
2 Instituto Militar de Engenharia, Praia Vermelha, Urca, Rio de Janeiro, RJ, CEP, Brazil
3 COPPE/UFRJ, Universidade Federal do Rio de Janeiro, RJ, PO Box 68.501, Brazil
E-mail: ricardo@cds.eb.mil.br, awallace@cos.ufrj.br, xexeo@cos.ufrj.br, jano@cos.ufrj.br
Abstract: This work proposes an algorithm that uses paths based on tile segmentation to build complex clusters. After allocating data items (points) to geometric shapes in tile format, the complexity of our algorithm is related to the number of tiles instead of the number of points. The main novelty is the way our algorithm goes through the grids, saving time and providing good results. It does not demand any configuration parameters from users, making easier to use than other strategies. Besides, the algorithm does not create overlapping clusters, which simplifies the interpretation of results.
Research Paper Link: http://dspace.chitkara.edu.in/jspui/bitstream/123456789/703/3/4-%20Path%20Clustering%20in%20a%20efficient%20way%20complex%20data%20-%20Fernandes.pdf
DOI: https://doi.org/10.15415/jotitt.2017.52004
ReplyDeleteYour post on path clustering and grouping in efficient systems was both enlightening and comprehensive. I appreciated how you broke down complex clustering techniques into easily digestible insights that highlight the importance of data organization in enhancing system performance. Your detailed analysis not only sheds light on the intricacies of efficient data grouping but also provides practical examples that make the subject accessible to both beginners and seasoned professionals. It’s clear that thoughtful organization is key to innovation and productivity in any field. For those considering improvements in their workspaces or home environments, I highly recommend checking out R for Remodelers. Their expertise in modern design and quality craftsmanship truly transforms spaces.