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[http://relearn.be/2015/etherdump/training-common-sense.html * notes taken during Relearn 2015, training common sense]<br>
[http://relearn.be/2015/etherdump/training-common-sense.html * notes taken during Relearn 2015, training common sense]<br>
[http://relearn.be/2015/etherdump/training-common-sense-pattern-readme-plus.md.html * #!PATTERN+.readme]
[http://relearn.be/2015/etherdump/training-common-sense-pattern-readme-plus.md.html * #!PATTERN+.readme]
[http://www.cqrrelations.constantvzw.org/1x0/the-annotator/ * the Annotator, Cqrrelations Jan. 2015], [http://pad.constantvzw.org/p/the_annotator on etherpad]<br>
[http://annotations.manettaberends.nl/txt/cqrrelations-jan-2015-day-1.html * notes Cqrrelations day 1], [http://annotations.manettaberends.nl/txt/cqrrelations-jan-2015-day-2.html day 2], [http://annotations.manettaberends.nl/txt/cqrrelations-jan-2015-day-3.html day 3], [http://annotations.manettaberends.nl/txt/cqrrelations-jan-2015-day-4.html day 4], [http://annotations.manettaberends.nl/txt/cqrrelations-jan-2015-day-5.html day 5]


==notes==
==notes==

Revision as of 19:19, 20 September 2015

#!PATTERN+

Clips patterns-scanner.jpg

info

Pattern+ is an annotated edition of the webmining module Pattern. The alpha-release of Pattern+ serves two interconnected goals: It is first of all an attempt to grow our understanding of - and concern with - the culture of data-mining, and then to feed this back into the practice of data-mining itself. It is also an experiment with forms of collaborative techno-critique that locate themselves closely to actual software objects. (from: #!PATTERN+.readme)

Contributors are Manetta Berends, Christina Colchoir, Frederic Janssens, Anne Laforet, My Lê, Femke Snelting, Kym Ward.


* earlier notes
* notes taken during Relearn 2015, training common sense
* #!PATTERN+.readme

* the Annotator, Cqrrelations Jan. 2015, on etherpad
* notes Cqrrelations day 1, day 2, day 3, day 4, day 5

notes

* problems related to the common-sense results:
- "it is only possible to categorise, after you have defined the categories" — Solon Barocas at Cqrrelations, 2015
- how can we escape the vicious circle  (of training by showing examples of current 'status quo')?
- when an algorithm is made to predict a certain 'truth', how does it find the unpredictable / margins?


related

* CLiPS Pattern, official website