Bibliography
A Data Mining Glossary, http://www.thearling.com/glossary.htm; consulted 13 April 2012
A Tutorial on Clustering Algorithms, http://home.dei.polimi.it/matteucc/Clustering/tutorial_html/; consulted 15 April 2012
Data mining for process improvement, http://www.crosstalkonline.org/storage/issue-archives/2011/201101/201101-Below.pdf; consulted 15 April 2012
Data mining techniques, http://www.obgyn.cam.ac.uk/cam-only/statsbook/stdatmin.html; consulted 15 April 2012
Data Mining: Text Mining. Visulization and social Media, http://datamining.typepad.com/data_mining/2010/12/more-thoughts-on-google-books-ngrams.html; consulted 13 April 2012
Data Mining: What is Data Mining?, http://www.anderson.ucla.edu/faculty/jason.frand/teacher/technologies/palace/datamining.htm; consulted 14 April 2012
Fabio Ciravegna, Mark Greengrass, Tim Hitchcock, Sam Chapman, Jamie Mc Laughlin and Ravish Bhagdev, ‘Finding Needles in the Haystacks: Data-mining in Distributed Historical Datasets’ in Mark Greengrass and Lorna Hughes, The virtual representation of the past (surrey, 2008) p.66
Introduction to data mining, http://www.youtube.com/watch?v=_QH4oIOd9nc; consulted 13 April 2012
New Methods for Humanities, research;http://people.lis.illinois.edu/~unsworth/lyman.htm; consulted 15 April 2012
Stephen Robertson, Understanding Inverse Document Frequency: On theoretical arguments for IDF, Journal of Documentation, 60 no. vol. 5, p. 1
Topic Modeling and Network Analysis, http://www.scottbot.net/HIAL/?p=221; consulted 18 April 2012
Topic models, http://videolectures.net/mlss09uk_blei_tm/; consulted 18 April 2012
Sapping Attention, http://sappingattention.blogspot.co.uk/;consulted 18 April 2012 With Criminal Intent, http://criminalintent.org/; consulted 18 April 2012
A Tutorial on Clustering Algorithms, http://home.dei.polimi.it/matteucc/Clustering/tutorial_html/; consulted 15 April 2012
Data mining for process improvement, http://www.crosstalkonline.org/storage/issue-archives/2011/201101/201101-Below.pdf; consulted 15 April 2012
Data mining techniques, http://www.obgyn.cam.ac.uk/cam-only/statsbook/stdatmin.html; consulted 15 April 2012
Data Mining: Text Mining. Visulization and social Media, http://datamining.typepad.com/data_mining/2010/12/more-thoughts-on-google-books-ngrams.html; consulted 13 April 2012
Data Mining: What is Data Mining?, http://www.anderson.ucla.edu/faculty/jason.frand/teacher/technologies/palace/datamining.htm; consulted 14 April 2012
Fabio Ciravegna, Mark Greengrass, Tim Hitchcock, Sam Chapman, Jamie Mc Laughlin and Ravish Bhagdev, ‘Finding Needles in the Haystacks: Data-mining in Distributed Historical Datasets’ in Mark Greengrass and Lorna Hughes, The virtual representation of the past (surrey, 2008) p.66
Introduction to data mining, http://www.youtube.com/watch?v=_QH4oIOd9nc; consulted 13 April 2012
New Methods for Humanities, research;http://people.lis.illinois.edu/~unsworth/lyman.htm; consulted 15 April 2012
Stephen Robertson, Understanding Inverse Document Frequency: On theoretical arguments for IDF, Journal of Documentation, 60 no. vol. 5, p. 1
Topic Modeling and Network Analysis, http://www.scottbot.net/HIAL/?p=221; consulted 18 April 2012
Topic models, http://videolectures.net/mlss09uk_blei_tm/; consulted 18 April 2012
Sapping Attention, http://sappingattention.blogspot.co.uk/;consulted 18 April 2012 With Criminal Intent, http://criminalintent.org/; consulted 18 April 2012