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• Wikipedia Infobox Generator Using Cross Lingual Unstructured Text
  * Clustering for aligning multiple language entity names based on page topic * Large scale data
  4 KB (604 words) - 03:59, 24 October 2011
• The Missing Link - A Probabilistic Model of Document Content and Hypertext Connectivity
  For clustering the hyperlinks, they use [[UsesMethod::PHITS]] which is mathematically iden * K. Bharat and M. R. Henzinger. Improved algorithms for topic distillation in hyperlinked environments.
  4 KB (610 words) - 17:08, 5 November 2012
• Syllabus for Machine Learning with Large Datasets 10-605 in Spring 2015
  * Tues Jan 20. [[Class meeting for 10-605 Streaming Naive Bayes|Streaming algorithms and Naive Bayes; The stream-and-sort design pattern; Naive Bayes for large * Thus Feb 19. [[Class meeting for 10-605 Randomized|Randomized Algorithms 1]]
  9 KB (1,328 words) - 14:50, 14 October 2015
• Machine Learning with Large Datasets 10-605 in Spring 2012
  ...vant to the course - e.g., to compare the scalability of variant learning algorithms on datasets. * Geographical names and places - data on places from GeoNames, Wikipedia, and Geo-tagged Flikr images.
  5 KB (716 words) - 11:34, 1 May 2012
• Syllabus for Machine Learning with Large Datasets 10-605 in Spring 2013
  * Wed Jan 23. [[Class meeting for 10-605 2013 01 23|Streaming algorithms and Naive Bayes; The stream-and-sort design pattern; Naive Bayes for large * Wed Jan 30. [[Class meeting for 10-605 2013 01 30|More on streaming algorithms: Rocchio, and theory of on-line learning]]
  7 KB (1,005 words) - 17:20, 10 January 2014
• Project Abstract - Bo, Kevin, Rushin
  • We store a persistent database of entities using this clustering, whereby each cluster represents a real-world entity. In other words, an en o For how many entities does a given attribute exist in the data?
  4 KB (675 words) - 18:19, 1 February 2011
• Project Abstract - Rushin, Kevin, Bo
  • We store a persistent database of entities using this clustering, whereby each cluster represents a real-world entity. In other words, an en o For how many entities does a given attribute exist in the data?
  5 KB (739 words) - 18:19, 1 February 2011
• Comparison Das et al WSDM 2011 and Zhao et al AAAI 2007
  ...n Proceedings of the fourth ACM international conference on Web search and data mining, 2011. [http://web.eecs.umich.edu/~congy/work/wsdm11.pdf] Both papers made use of algorithms from time series models and graph clustering to solve their respective problems.
  5 KB (842 words) - 23:49, 5 November 2012
• ToWikify
  ..._WWW2009]] || [[Preserving the privacy of sensitive relationships in graph data. PinKDD, 2007]] [http://www.springerlink.com/content/n1404m0668452854/] || ...supervised_learning_algorithm_for_link_prediction]] || [[Fast and scalable algorithms for semi-supervised link prediction on static and dynamic graphs]] [http://
  12 KB (1,642 words) - 17:02, 30 November 2012
• Project Anuj Dani Somanchi
  ...hus does not need tweet ranking. As the time goes on, we will acquire more data from him, so we can recommend accordingly. ...ted in we want to use the learnt graph from the previous step and then use algorithms for link prediction to the nodes which are tweets. Given a graph G(V, E), w
  15 KB (2,240 words) - 23:45, 14 February 2011
• Miray Dongyang Niting project proposal
  ...particular research area looking at the changes in the currently available data. Algorithms, Sociology, Signal Processing.
  15 KB (2,315 words) - 00:18, 15 February 2011
• Expectation–maximization algorithm
  |title=Maximum Likelihood from Incomplete Data via the EM Algorithm |title=Maximum likelihood theory for incomplete data from an exponential family
  39 KB (5,817 words) - 21:17, 26 September 2012
• Project Anuj Dani
  ...activity (# of tweets posted on Twitter), while [15] did this by means of clustering email-exchange network graph. In topic modeling to model document network data, [19] proposed relation topic models for document networks, [19] proposed a
  12 KB (1,759 words) - 16:03, 3 February 2011

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