@electronic{vlado.fmf.uni-lj.si,
   title       = {Software Three Dimensional Blockmodeling}, 
   url         = {http://vlado.fmf.uni-lj.si/pub/networks/progs/R/ibm3m.zip},
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@electronic{cscs.umich.edu,
   title       = {Community Discovery Methods for Complex Networks}, 
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@electronic{www.carrot2.org,
   title       = {Carrot2 project}, 
   url         = {http://www.carrot2.org/website/xml/index.xml},
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@electronic{www.stat.washington.edu,
   title       = {Adrian Raftery: Unpublished Technical Reports}, 
   url         = {http://www.stat.washington.edu/raftery/Research/techreports.html},
   biburl      = {https://puma.uni-kassel.de/url/f250da443c58a43e16e029a24ef674f1/hotho},
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   description = {Handcock, M.S., Raftery, A.E. and Tantrum, J. (2005).

Model-Based Clustering for Social Networks.
Working Paper no. 46, Center for Statistics and the Social Sciences,
University of Washington.},
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@electronic{kt.ijs.si,
   title       = {Text-Garden -- Text-Mining Software Tools}, 
   url         = {http://kt.ijs.si/Dunja/textgarden/},
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@electronic{www.cs.cas.cz,
   title       = {Cluster list of papers}, 
   url         = {http://www.cs.cas.cz/~petra/Liter-Odkazy-shluk.html},
   biburl      = {https://puma.uni-kassel.de/url/fdf06acaed2194b64f1c93b6611d5b5d/hotho},
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@electronic{www.isi.edu,
   title       = {CBC}, 
   url         = {http://www.isi.edu/~pantel/Content/Demos/LexSem/cbc.htm},
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@electronic{www.informatics.bangor.ac.uk,
   title       = {dataset}, 
   url         = {http://www.informatics.bangor.ac.uk/~kuncheva/activities/artificial_data.htm},
   biburl      = {https://puma.uni-kassel.de/url/4b0a4d764b88f9156db9d957a12e9f50/hotho},
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@electronic{www.mathematik.uni-marburg.de,
   title       = {Fundamental Clustering Problem Suite | Databionics}, 
   url         = {http://www.mathematik.uni-marburg.de/~databionics/en//?q=data},
   biburl      = {https://puma.uni-kassel.de/url/5c022da9b82207748adb130218135031/hotho},
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@electronic{www.di.ubi.pt,
   title       = {| Gaël Harry Dias - Department of Computer Science - UBI}, 
   url         = {http://www.di.ubi.pt/~ddg/?op=paginas/publications.html},
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   keywords    = {clustering to:bibtex similarity ol measure},
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   description = {- Dias, G. & Alves, E. (2005). Language-Independent Informative Topic Segmentation. In Proceedings of the 9th International Symposium on Social Communication. Santiago de Cuba, Cuba, January 24-28. pp. 588-592. ISBN: 9597174057. [pdf]},
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@electronic{www.cs.albany.edu,
   title       = {Ian Davidson, Mining, Machine Learning, MML, Data Mining}, 
   url         = {http://www.cs.albany.edu/~davidson/},
   biburl      = {https://puma.uni-kassel.de/url/ea68f93bf7c8392fcdb46c085bf8c331/hotho},
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@electronic{websom.hut.fi,
   title       = {WEBSOM - A novel SOM-based approach to free-text mining}, 
   url         = {http://websom.hut.fi/websom/},
   biburl      = {https://puma.uni-kassel.de/url/6cac42474b296c0f9a58bb72a67e7472/hotho},
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@electronic{www.citeulike.org,
   title       = {CiteULike: Tag clustering}, 
   url         = {http://www.citeulike.org/tag/clustering},
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@electronic{snaket.di.unipi.it,
   title       = {Search SnakeT Clustering Engine, Meta Search Cluster MetaSearch}, 
   url         = {http://snaket.di.unipi.it/},
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@electronic{clusty.com,
   title       = {Clusty the Clustering Engine}, 
   url         = {http://clusty.com/},
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@electronic{vivisimo.com,
   title       = {Vivísimo // Vivisimo Clustering - automatic categorization and meta-search software}, 
   url         = {http://vivisimo.com/},
   biburl      = {https://puma.uni-kassel.de/url/2cfe418315b33f61be32074a1b52892b/hotho},
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@electronic{www.cs.rutgers.edu,
   title       = {Data Clustering: A Review}, 
   url         = {http://www.cs.rutgers.edu/~mlittman/courses/lightai03/jain99data.pdf},
   biburl      = {https://puma.uni-kassel.de/url/e17b7bd1a05155a49f881b2246154f84/hotho},
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@electronic{www.csee.umbc.edu,
   title       = {Tutorial on Document Clustering}, 
   url         = {http://www.csee.umbc.edu/~nicholas/clustering/},
   biburl      = {https://puma.uni-kassel.de/url/e8417ba93ffa0fd098e60d256fdb568b/hotho},
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@electronic{www.i-cherubini.it,
   title       = {Spatial Clustering Methods in Data Mining: A Survey at Mauro Cherubini’s moleskine}, 
   url         = {http://www.i-cherubini.it/mauro/blog/2005/09/21/spatial-clustering-methods-in-data-mining-a-survey/},
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   keywords    = {clustering to:bibtex survey},
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   description = {J. Han, M. Kamber, and A. K. H. Tung. Geographic Data Mining and Knowledge Discovery, chapter Spatial Clustering Methods in Data Mining: A Survey, pages 1–29. Taylor and Francis, 2001. [url]},
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@electronic{crd.lbl.gov,
   title       = {Chris Ding Publications}, 
   url         = {http://crd.lbl.gov/~cding/papers/spectral.html},
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