Análisis de grupos (Spanish Wikipedia)

Analysis of information sources in references of the Wikipedia article "Análisis de grupos" in Spanish language version.

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20doi.org

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araa.asn.au

Bewley, A., & Upcroft, B. (2013). Advantages of Exploiting Projection Structure for Segmenting Dense 3D Point Clouds. In Australian Conference on Robotics and Automation [1]

archive.org

Can, F.; Ozkarahan, E. A. (1990). «Concepts and effectiveness of the cover-coefficient-based clustering methodology for text databases». ACM Transactions on Database Systems 15 (4): 483. doi:10.1145/99935.99938.
Manning, Christopher D.; Raghavan, Prabhakar; Schütze, Hinrich (2008). Introduction to Information Retrieval. Cambridge University Press. ISBN 978-0-521-86571-5.
Rand, W. M. (1971). «Objective criteria for the evaluation of clustering methods». Journal of the American Statistical Association (American Statistical Association) 66 (336): 846-850. JSTOR 2284239. doi:10.2307/2284239.

arxiv.org

Kraskov, Alexander; Stögbauer, Harald; Andrzejak, Ralph G.; Grassberger, Peter (1 de diciembre de 2003) [28 November 2003]. Hierarchical Clustering Based on Mutual Information. arXiv:q-bio/0311039.

doi.org

dx.doi.org

Estivill-Castro, Vladimir (20 de junio de 2002). «Why so many clustering algorithms — A Position Paper». ACM SIGKDD Explorations Newsletter 4 (1): 65-75. doi:10.1145/568574.568575.
Sibson, R. (1973). «SLINK: an optimally efficient algorithm for the single-link cluster method». The Computer Journal (British Computer Society) 16 (1): 30-34. doi:10.1093/comjnl/16.1.30.
Defays, D. (1977). «An efficient algorithm for a complete link method». The Computer Journal (British Computer Society) 20 (4): 364-366. doi:10.1093/comjnl/20.4.364.
Lloyd, S. (1982). «Least squares quantization in PCM». IEEE Transactions on Information Theory 28 (2): 129-137. doi:10.1109/TIT.1982.1056489.
Kriegel, Hans-Peter; Kröger, Peer; Sander, Jörg; Zimek, Arthur (2011). «Density-based Clustering». WIREs Data Mining and Knowledge Discovery 1 (3): 231-240. doi:10.1002/widm.30. Archivado desde el original el 17 de noviembre de 2016. Consultado el 15 de enero de 2016.
Achtert, E.; Böhm, C.; Kröger, P. (2006). «DeLi-Clu: Boosting Robustness, Completeness, Usability, and Efficiency of Hierarchical Clustering by a Closest Pair Ranking». LNCS: Advances in Knowledge Discovery and Data Mining. Lecture Notes in Computer Science 3918: 119-128. ISBN 978-3-540-33206-0. doi:10.1007/11731139_16.
Can, F.; Ozkarahan, E. A. (1990). «Concepts and effectiveness of the cover-coefficient-based clustering methodology for text databases». ACM Transactions on Database Systems 15 (4): 483. doi:10.1145/99935.99938.
Agrawal, R.; Gehrke, J.; Gunopulos, D.; Raghavan, P. (2005). «Automatic Subspace Clustering of High Dimensional Data». Data Mining and Knowledge Discovery 11: 5. doi:10.1007/s10618-005-1396-1.
Achtert, E.; Böhm, C.; Kriegel, H. P.; Kröger, P.; Müller-Gorman, I.; Zimek, A. (2006). «Finding Hierarchies of Subspace Clusters». LNCS: Knowledge Discovery in Databases: PKDD 2006. Lecture Notes in Computer Science 4213: 446-453. ISBN 978-3-540-45374-1. doi:10.1007/11871637_42.
Achtert, E.; Böhm, C.; Kriegel, H. P.; Kröger, P.; Müller-Gorman, I.; Zimek, A. (2007). «Detection and Visualization of Subspace Cluster Hierarchies». LNCS: Advances in Databases: Concepts, Systems and Applications. Lecture Notes in Computer Science 4443: 152-163. ISBN 978-3-540-71702-7. doi:10.1007/978-3-540-71703-4_15.
Achtert, E.; Böhm, C.; Kröger, P.; Zimek, A. (2006). «Mining Hierarchies of Correlation Clusters». Proc. 18th International Conference on Scientific and Statistical Database Management (SSDBM): 119-128. ISBN 0-7695-2590-3. doi:10.1109/SSDBM.2006.35.
Böhm, C.; Kailing, K.; Kröger, P.; Zimek, A. (2004). «Computing Clusters of Correlation Connected objects». Proceedings of the 2004 ACM SIGMOD international conference on Management of data - SIGMOD '04. p. 455. ISBN 1581138598. doi:10.1145/1007568.1007620.
Achtert, E.; Bohm, C.; Kriegel, H. P.; Kröger, P.; Zimek, A. (2007). «On Exploring Complex Relationships of Correlation Clusters». 19th International Conference on Scientific and Statistical Database Management (SSDBM 2007). p. 7. ISBN 0-7695-2868-6. doi:10.1109/SSDBM.2007.21.
Meilă, Marina (2003). «Comparing Clusterings by the Variation of Information». Learning Theory and Kernel Machines. Lecture Notes in Computer Science 2777: 173-187. ISBN 978-3-540-40720-1. doi:10.1007/978-3-540-45167-9_14.
Frey, B. J.; Dueck, D. (2007). «Clustering by Passing Messages Between Data Points». Science 315 (5814): 972-976. PMID 17218491. doi:10.1126/science.1136800.
Dunn, J. (1974). «Well separated clusters and optimal fuzzy partitions». Journal of Cybernetics 4: 95-104. doi:10.1080/01969727408546059.
Pfitzner, Darius; Leibbrandt, Richard; Powers, David (5 de julio de 2008). «Characterization and evaluation of similarity measures for pairs of clusterings». Knowledge and Information Systems (en inglés) 19 (3): 361. ISSN 0219-3116. doi:10.1007/s10115-008-0150-6. Consultado el 12 de abril de 2021.
Pourrajabi, M.; Moulavi, D.; Campello, R. J. G. B.; Zimek, A.; Sander, J.; Goebel, R. (2014). «Model Selection for Semi-Supervised Clustering». Proceedings of the 17th International Conference on Extending Database Technology (EDBT),. pp. 331-342. doi:10.5441/002/edbt.2014.31.
Rand, W. M. (1971). «Objective criteria for the evaluation of clustering methods». Journal of the American Statistical Association (American Statistical Association) 66 (336): 846-850. JSTOR 2284239. doi:10.2307/2284239.

doi.org

Pfitzner, Darius; Leibbrandt, Richard; Powers, David (5 de julio de 2008). «Characterization and evaluation of similarity measures for pairs of clusterings». Knowledge and Information Systems (en inglés) 19 (3): 361. ISSN 0219-3116. doi:10.1007/s10115-008-0150-6. Consultado el 12 de abril de 2021.

gsu.edu

cs.gsu.edu

Sibson, R. (1973). «SLINK: an optimally efficient algorithm for the single-link cluster method». The Computer Journal (British Computer Society) 16 (1): 30-34. doi:10.1093/comjnl/16.1.30.

issn.org

portal.issn.org

Pfitzner, Darius; Leibbrandt, Richard; Powers, David (5 de julio de 2008). «Characterization and evaluation of similarity measures for pairs of clusterings». Knowledge and Information Systems (en inglés) 19 (3): 361. ISSN 0219-3116. doi:10.1007/s10115-008-0150-6. Consultado el 12 de abril de 2021.

jstor.org

Rand, W. M. (1971). «Objective criteria for the evaluation of clustering methods». Journal of the American Statistical Association (American Statistical Association) 66 (336): 846-850. JSTOR 2284239. doi:10.2307/2284239.

microsoft.com

academic.research.microsoft.com

Microsoft academic search: most cited data mining articles Archivado el 21 de abril de 2010 en Wayback Machine.: DBSCAN is on rank 24, when accessed on: 4/18/2010

nih.gov

ncbi.nlm.nih.gov

Frey, B. J.; Dueck, D. (2007). «Clustering by Passing Messages Between Data Points». Science 315 (5814): 972-976. PMID 17218491. doi:10.1126/science.1136800.

oregonstate.edu

eecs.oregonstate.edu

Färber, Ines; Günnemann, Stephan; Kriegel, Hans-Peter; Kröger, Peer; Müller, Emmanuel; Schubert, Erich; Seidl, Thomas; Zimek, Arthur (2010). «On Using Class-Labels in Evaluation of Clusterings». En Fern, Xiaoli Z.; Davidson, Ian; Dy, Jennifer, eds. MultiClust: Discovering, Summarizing, and Using Multiple Clusterings. ACM SIGKDD.

psu.edu

citeseerx.ist.psu.edu

Jain, Anil K. (2012). «Data Clustering: 50 Years Beyond K-Means». Michigan State University.

web.archive.org

Kriegel, Hans-Peter; Kröger, Peer; Sander, Jörg; Zimek, Arthur (2011). «Density-based Clustering». WIREs Data Mining and Knowledge Discovery 1 (3): 231-240. doi:10.1002/widm.30. Archivado desde el original el 17 de noviembre de 2016. Consultado el 15 de enero de 2016.
Microsoft academic search: most cited data mining articles Archivado el 21 de abril de 2010 en Wayback Machine.: DBSCAN is on rank 24, when accessed on: 4/18/2010

wiley.com

wires.wiley.com

Kriegel, Hans-Peter; Kröger, Peer; Sander, Jörg; Zimek, Arthur (2011). «Density-based Clustering». WIREs Data Mining and Knowledge Discovery 1 (3): 231-240. doi:10.1002/widm.30. Archivado desde el original el 17 de noviembre de 2016. Consultado el 15 de enero de 2016.