User:Manetta/meta-mining/PATTERN+: Difference between revisions

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


==Relearn==
Pattern+ is initiated as a project during the Relearn summerschool 2015 in Brussels.


===material from Relearn 2015===
[[User:Manetta/meta-mining/knowledge-discovery-in-data|* Knowledge Discovery in Data (KDD) steps]]<br>
[[User:Manetta/meta-mining/data-mining-culture|* data mining culture]]<br>
===other resources===
[http://pad.constantvzw.org/p/commonsense * earlier notes (Jul. 2015)]<br>
[http://pad.constantvzw.org/p/commonsense * earlier notes (Jul. 2015)]<br>
[http://relearn.be/2015/etherdump/training-common-sense.html * notes taken during Relearn Aug. 2015, training common sense]<br>
[http://relearn.be/2015/etherdump/training-common-sense.html * notes taken during Relearn Aug. 2015, training common sense]<br>
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==related==
==related==
[http://relearn.be/2015/ * Relearn website]<br>
[http://www.clips.ua.ac.be/pages/pattern * CLiPS Pattern, official website]<br>
[http://www.clips.ua.ac.be/pages/pattern * CLiPS Pattern, official website]<br>



Revision as of 14:02, 19 November 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.

Relearn

Pattern+ is initiated as a project during the Relearn summerschool 2015 in Brussels.

material from Relearn 2015

* Knowledge Discovery in Data (KDD) steps
* data mining culture

other resources

* earlier notes (Jul. 2015)
* notes taken during Relearn Aug. 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

* Relearn website
* CLiPS Pattern, official website